Download the MP3 Date: June 19, 2015 By: Aaron Delp and Brian Gracely Description: Aaron and Brian talk to Chip Childers (@chipchilders, VP of Technology @CloudFoundryOrg) about the current status of Cloud Foundry projects, how Microsoft .NET will be integrated, IaaS vs. PaaS, and the CF.org thinking about overall interoperability Interested in the O'Reilly OSCON? Want to register for OSCON now? Use promo code 20CLOUD for 20% off Details to win an OSCON pass coming soon! Check out the OSCON Schedule Free eBook from O'Reilly Media for Cloudcast Listeners! Check out an excerpt from the upcoming Docker Cookbook Topic 1 - From an overall project perspective, what grades would you give Cloud Foundry in terms of stability, core functionality, security, operations, etc? Topic 2 - You were previously involved (directly/indirectly)with CloudStack. As you talk to people in the marketplace, how is it different discussing IaaS vs. PaaS. Topic 3 - How much ability will you have to drive prioritization within sub-projects or new projects? (eg. Security vs. new Languages vs. Interop, etc.) Topic 4 - What’s the CF.org way of thinking about interoperability? Topic 5 - What guidance are you giving the teams in terms of expandability of Cloud Foundry? Architecturally, are there certain places you recommend over other places? Topic 6 - Is there a place for integrating SaaS applications (monitoring, logging, etc.) into Cloud Foundry?

CoreOS Linux is the operating system for “Super Massive Deployments”. We wanted to see how easily we can get CoreOS logs into Elasticsearch / ELK-powered centralized logging service. Here’s how to get your CoreOS logs into ELK in about 5 minutes, give or take. If you’re familiar with CoreOS and Logsene, you can grab CoreOS/Logsene config files from Github. Here’s an example Kibana Dashboard you can get in the end: CoreOS Kibana Dashboard CoreOS is based on the following: Docker and rkt for containers systemd for startup scripts, and restarting services automatically etcd as centralized configuration key/value store fleetd to distribute services over all machines in the cluster. Yum. journald to manage logs. Another yum. Amazingly, with CoreOS managing a cluster feels a lot like managing a single machine! We’ve come a long way since ENIAC! There’s one thing people notice when working with CoreOS – the repetitive inspection of local or remote logs using “journalctl -M machine-N -f | grep something“. It’s great to have easy access to logs from all machines in the cluster, but … grep? Really? Could this be done better? Of course, it’s 2015! Here is a quick example that shows how to centralize logging with CoreOS with just a few commands. The idea is to forward the output of “journalctl -o short” to Logsene‘s Syslog Receiver and take advantage of all its functionality – log searching, alerting, anomaly detection, integrated Kibana, even correlation of logs with Docker performance metrics — hey, why not, it’s all available right there, so we may as well make use of it all! Let’s get started! Preparation: 1) Get a list of IP addresses of your CoreOS machines fleetctl list-machines 2) Create a new Logsene App (here) 3) Change the Logsene App Settings, and authorize the CoreOS host IP Addresses from step 1) (here’s how/where) Congratulations – you just made it possible for your CoreOS machines to ship their logs to your new Logsene app! Test it by running the following on any of your CoreOS machines: journalctl -o short -f | ncat --ssl logsene-receiver-syslog.sematext.com 10514 …and check if the logs arrive in Logsene (here). If they don’t, yell at us @sematext – there’s nothing better than public shaming on Twitter to get us to fix things. :) Create a fleet unit file called logsene.service [Unit] Description=Logsene Log Forwarder [Service] Restart=always RestartSec=10s ExecStartPre=/bin/sh -c "if [ -n \"$(etcdctl get /sematext.com/logsene/`hostname`/lastlog)\" ]; then echo \"Value Exists: /sematext.com/logsene/`hostname`/lastlog $(etcdctl get /sematext.com/logsene/`hostname`/lastlog)\"; else etcdctl set /sematext.com/logsene/`hostname`/lastlog\"`date +\"%Y-%%m-%d %%H:%M:%S\"`\"; true; fi" ExecStart=/bin/sh -c "journalctl --since \"$(etcdctl get /sematext.com/logsene/`hostname`/lastlog)\" -o short -f | ncat --ssl logsene-receiver-syslog.sematext.com 10514" ExecStopPost=/bin/sh -c "export D=\"`date +\"%Y-%%m-%%d %%H:%M:%S\"`\"; /bin/etcdctl set /sematext.com/logsene/$(hostname)/lastlog \"$D\"" [Install] WantedBy=multi-user.target [X-Fleet] Global=true Activate cluster-wide logging to Logsene with fleet To start logging to Logsene from all machines activate logsene.service: fleetctl load logsene.service fleetctl start logsene.service There. That’s all there is to it! Hope this worked for you! At this point all your CoreOS logs should be going to Logsene. Now you have a central place to see all your CoreOS logs. If you want to send your app logs to Logsene, you can do that, too — anything that can send logs via Syslog or to Elasticsearch can also ship logs to Logsene. If you want some Docker containers & host monitoring to go with your CoreOS logs, just pull spm-agent-docker from Docker Registry. Enjoy!

I have just recorded a 5 minute video that demonstrates running an out of stock example from Apache Camel release, the camel-example-servlet packaged as a docker container and running on a kubernetes platform, such as openshift 3. camel-servlet-example scaled up to 3 running containers (pods) which is easy with kubernetes and fabric8 In this video I have already deployed the example and then demonstrates how we can use the fabric8 web console to manage our application. And also connect to the running container and see inside, such as the Camel routes visually as shown above. Then I run a simple bash script from my laptop that sends a HTTP GET to the Camel example and prints the response. The script runs in a endless loop and demonstrates how kubernetes can easily scale up and down multiple Camel containers and load balance across the running containers. And at the end its even self healing when I force killing docker containers. So I suggest to grab a fresh cup of tea or coffee and sit back and play the 5 minutes video. The video is hosted on vimeo and can be seen from this link.

The growth of Azure has been outstanding--more than 90,000 new subscriptions every month. And the innovation is exponential with over 500 new features and services being added to the platform in the last 12 months. We're very excited to be part of this growth. As we announced yesterday, you can now access Stackato through Azure. We think it's a great way for Azure customers to get access to a Cloud Foundry and Docker based PaaS. With Azure, Microsoft provides an easy path to the cloud for their customers. All applications can be run on one cloud. Microsoft wants to dominate the cloud the same as it has with on-premise software and rarely does a day go by without reading an article about Azure. Whether it's their recent announcement to help encourage start-up's use of Azure by providing $120,000 worth of credits per year or their commitment to open source. Azure gives its customers a growing collection of integrated services that make it easier to build and manage enterprise, mobile, web and Internet of Things (IoT) apps faster. Enterprises face real complexities when building their cloud solution. Having a solid infrastructure is really just the first step in the process--companies also need the right platform to support the deployment and management of their cloud-native applications. The platform should give their developers the freedom to use the language best suited to build the application. In addition, enterprises are on more than one cloud. They need to have the versatility to scale out or move their applications to whatever cloud is appropriate in order to meet end user demand without any downtime. With Stackato, we help remove these complexities. We provide enterprises with a polyglot PaaS that supports the development of applications in virtually any language. We like to refer to Stackato as being "infrastructure-agnostic" and allow companies to deploy their applications to any cloud--private, public or hybrid--without the need to run new scripts or re-package the application in order for it to work in the new environment. The combination of Stackato on Azure gives enterprises the technology they need to streamline application delivery, drive innovation and meet the demands of their customers.

We’re going back to the classics this month, with the latest enterprise collaboration news round-up focussing on cloud strategy and considerations and benefits when it comes to implementing collaboration software. Mashable shared an infographic it created in conjunction with Hewlett Packard, which compiles data and research suggesting that the use of hybrid and private cloud computing is on the rise. The article quotes statistics from Rightscale, which states that 82% of enterprises have a multi-cloud strategy already, and of these 14% use multiple private clouds, 13% use multiple public clouds, and 55% use hybrid clouds. Mashable quotes Technology Business Research, which states that “there is continued migration of enterprise vendors in mature markets such as the U.S. to hybrid and private cloud platforms to provide software vendors an opportunity to generate adoption for management technologies, as customers require next-generation tools to manage heterogeneous IT infrastructures efficiently.” In his article for eWEEK, Chris Preimesberger outlines 10 ways IT and business leaders must collaborate on cloud strategies. Chris explains that a decision to use cloud services is no longer simply down to the IT department. During the last nine years, he says, entire businesses have become necessarily immersed in IT strategies in order to harness the cloud for economics, innovation, operations and growth. He shares a slide show which provides advice for how technical and business leaders can collaborate to build a secure cloud strategy. The slide show states that usage indicate that private clouds are expected to grow at double the rate of public cloud, a result of ongoing concerns about data security and privacy. Gary Audin asks the question cloud economics or flexibility? in his article for No Jitter. Gary explains that although the cost of cloud can be attractive, that might not be the real draw for enterprises. He states that knowing what costs to consider as part of a cloud service implementation is vital to making the right decision about cloud. Gary points out the benefits of the cloud as being far more than simply a matter of cost. He explains that the cloud allows rapid response for an enterprise as it contends with change due to situations such as staff growth or reduction, market fluctuations, financial limitations, or new opportunities. Above all, Gary explains, the cloud delivers flexibility and it is this which makes it the most attractive option for enterprises. In his article for MSP Mentor, Michael Brown reveals the result of a recent report on cloud adoption in the enterprise. The report, by Skyhigh Networks, revealed that enterprise cloud adoption grew by 43% in 2014. Michael highlights findings on the file sharing front, revealing that 37 percent of employees were found to be uploading sensitive business data to consumer file sharing services. Consumer file sharing services are one element of a growing trend towards BYOC (bring your own cloud, content and collaboration). Robert Bamforth explains that BYOC is an evolution of BYOD (bring your own device) which posed a challenge to IT departments since the rise of the smartphone. Robert explains that BYOC is a new challenge for IT departments in controlling their organisation’s digital assets while liberating employee productivity and information sharing. Robert states that the BYOC conundrum should change as enterprise-strength security features and tools continue to evolve to have more consumer-like interfaces, which will make asking employees to use enterprise tools much easier. He gives some suggestions to help enterprises in the mean time: understand the appeal of consumer tools, make sure everyone understands security risks, forget trying to apply strong rules to trivial information, get a mobile-ready solution, look for and pre-plug data leaks, and above all don’t stop collaboration if it’s happening. In his article for ZDNet, Dion Hinchcliffe reflects on the state of the digital collaboration industry. Far from maturing, Dion says, the collaboration tool space is busier than ever evolving, branching out, and multiplying. But, he asks, are organizations able to adopt so many different ways of working together? Dion observes that instead of settling down, the collaboration software space is actually get more interesting and varied, and he is seeing new technologies, such as applications that focus on optimizing collaboration for mobile devices or for team analytics. It’s now time for organizations to design a strong foundation for digital collaboration, says Dion, as the near future promises many key new innovations that must be considered and incorporated to stay competitive, both to customers and the workforce. When businesses do decide to adopt one or more digital collaboration platforms, Andre Bourque offers some helpful ways in which to measure ROI. Andre quotes a Mashable report which states that cloud collaboration drives creativity and engagement, leading to happier employees and a better company culture, but this is not a metric that is easily measurable. Andre explains that it’s hard to find definitive examples of ROI, as most are anecdotal or “in process”, and merely counting user adoption rate of a collaborative platform is inadequate. Instead, Andre quotes Angela Ashenden, of MWD Advisors, who offers the following metrics to consider: reduced travel time and costs; creating new business opportunities and services; increased employee retention rates, cost savings across the organisation, and faster on-boarding for new users. Do you have any metrics that you find useful to measure ROI on your collaboration platform in your organisation?

Docker deployments can be very dynamic with containers being started and stopped, moved around the YARN or Mesos-managed clusters, having very short life spans (the so-called pets) or long uptimes (aka cattle). Getting insight into the current and historical state of such clusters goes beyond collecting container performance metrics and sending alert notifications. If a container dies or gets paused, for example, you may want to know about it, right? Or maybe you’d want to be able to see that a container went belly up in retrospect when troubleshooting, wouldn’t you? Just two weeks ago we added Docker Monitoring (docker image is right here for your pulling pleasure) to SPM. We didn’t stop there — we’ve now expanded SPM’s Docker support by adding Docker Event collection, charting, and correlation. Every time a container is created or destroyed, started, stopped, or when it dies, spm-agent-docker captures the appropriate event so you can later see what happened where and when, correlate it with metrics, alerts, anomalies — all of which are captured in SPM — or with any other information you have at your disposal. The functionality and the value this brings should be pretty obvious from the annotated screenshot below. Like this post? Please tweet about Docker Events and Docker Metrics Monitoring Know somebody who’d find this post useful? Please let them know… Here’s the list of Docker events SPM Docker monitoring agent currently captures: Version Information on Startup: server-info – created by spm-agent framework with node.js and OS version info on startup docker-info – Docker Version, API Version, Kernel Version on startup Docker Status Events: Container Lifecycle Events like create, exec_create, destroy, export Container Runtime Events like die, exec_start, kill, oom, pause, restart, start, stop, unpause Every time a Docker container emits one of these events spm-agent-docker will capture it in real-time, ship it over to SPM, and you’ll be able to see it as shown in the above screenshot. Oh, and if you’re running CoreOS, you may also want to see how to index CoreOS logs into ELK/Logsene. Why? Because then you can have not only metrics and container events in one place, but also all container and application logs, too! If you’re using Docker, we hope you find this useful! Anything else you’d like us to add to SPM (for Docker or anyother integration)? Leave a comment, ping @sematext, or send us email – tell us what you’d like to get for early Christmas!

Leading today, VentureBeat reports on the quiet launch of Google’s Cloud Source Repositories. This seems like something we should have heard more about, but I don’t remember seeing anything about it. Amazon AWS announces the availability of all things Alexa, the Skills Kit, the Voice Service and a Fund. Last but not least, we have AJ Kohn, from Blind Five Year Old, talking about click-through rate being a ranking signal on Google’s search results. I don’t talk about SEO much, but reading AJ’s work is always fascinating. As always, enjoy today’s items, and please participate in the discussions on these sites. Top Stories Google has quietly launched a GitHub competitor, Cloud Source Repositories | VentureBeat Alexa Skills Kit, Alexa Voice Service, Alexa Fund | AWS Official Blog Startups, Career and Process Why offices are where work goes to die | Swizec Teller Unleashing the power of small teams | Andreas Papathanasis What Is A Tester? | Developsense Blog What happens when you stop relying on resumes | Aline Lerner Design and Development Swift 2: SIMD | Russ Bishop Why is Git better than Mercurial? | Javalobby Create a Maven archetype | Javalobby pip -t: A simple and transparent alternative to virtualenv | Zoomer Analytics Killing Off Wasabi – Part 1 | Fog Creek Blog WebAssembly- Explained | Modus Create Generating JSON Schema from XSD with JAXB and Jackson | Inspired by Actual Events AI, Machine Learning, Research and Advanced Algorithms Applying Machine Learning to Text Mining with Amazon S3 and RapidMiner | Amazon AWS Big Data, Visualization, SQL and NoSQL Is Click Through Rate A Ranking Signal? | Blind Five Year Old Cache-friendly binary search | Bannalia Discovering the Computer Science Behind Postgres Indexes | Java Code Geeks How an open-source competitive benchmark helped to improve databases | ArangoDB Security, Encryption and Cryptography Cracking JXcore… Again | Mark Haase Link Collections The Daily Six Pack: June 25, 2015 | Dirk Strauss Double Shot #1517 | A Fresh Cup Dew Drop – June 25, 2015 (#2042) | Morning Dew The Daily Six Pack: June 26, 2015 | Dirk Strauss

The use of OpenStack in the private cloud is invaluable for DevOps. It provides engineers the ability to innovate quickly and deal with uncertainty. It also maximizes existing infrastructure and provides a programmable, software-defined IaC. Openstack in the private cloud = agile development OpenStack has emerged as the de facto standard for IaaS in the private cloud. It gives engineers a vital self-service capability to provision (and de-provision) environments, allowing them to act autonomously, in the moment. This helps to eliminate the downstream bottleneck caused by waiting for operations staff to find time to do the provisioning. As OpenStack is open source it is vendor agnostic, allowing you to take advantage of competitive pricing rather than suffering from vendor lock-in. A private cloud means lower cost for the same capacity in a public cloud, which is especially useful for enterprises with high data needs. For security reasons, OpenStack is still mainly used in the private cloud by developers and QA, i.e. in a non-production context. However, OpenStack gives an ability to optimize application performance and/or security by having more control compared to public cloud. The software is increasingly backed by the critical mass of leading IT infrastructure vendors such as IBM, CICSO and HP. Gartner assumes that “by 2019, OpenStack enterprise deployments will grow tenfold, up from just hundreds of production deployments today, due to increased maturity and growing ecosystem support.”1 Challenges to consider OpenStack implementation skills are still rare in the market, so experimentation and self-learning is necessary. Although this takes time, it is offset by the fact the software is free and represents a good opportunity to gain internal expertise. This is particularly valid if you class infrastructure as a core competence. The maturity and functionality of OpenStack projects vary widely - while it covers storage, network and compute, the main adoption currently happens around compute (Nova) and block storage (Cinder), with object storage and network (Neutron) lacking significantly behind. However, without leveraging virtualized network services as part of a private cloud, full-stack environment provisioning is not possible, so don’t forget to add necessary network services to your private cloud. Where to begin Integrating OpenStack clouds with existing infrastructure can be a challenge. It is hardly plug and play. At first, it is best to focus on relatively isolated DevOps environments, such as Gartner’s “mode two”2 applications rather than introducing open stack across the board straight away, (Bimodal IT “refers to having two modes of IT, each designed to develop and deliver information – and technology – intensive services in its own way. Mode 1 is traditional, emphasizing scalability, efficiency, safety and accuracy. Mode 2 is nonsequential, emphasizing agility and speed.”3) As with any open source software, new functions and upgrades are frequently released. This means keeping up with changes in functionality and filling gaps with customizations or third-party products. Upgrades are complex and typically require planned downtime. For these reasons, we recommend choosing a hardened distribution and sticking with it. Openstack is the most complete vendor agnostic solution for storage, network and compute services. The ability for developers to instantly spin up environments at any time is invaluable for a fully agile DevOps environment, and is well worth the effort it takes to acclimatize to Openstack. 1 http://www.prnewswire.com/news-releases/suse-openstack-cloud-5-to-simplify-private-cloud-management-300048721.html 2 http://www.gartner.com/it-glossary/bimodal 3 http://www.gartner.com/it-glossary/bimodal

BQ deploys its call centre and telephony solution on Interoute Virtual Data Centre to improve international customer and employee communications Madrid, June 25th, 2015 - Interoute, owner operator of Europe's largest cloud services platform has announced that BQ, a leading European technology company, has chosen Interoute Virtual Data Centre (VDC), to host its new customer and employee unified communications solution. BQ has deployed a new telephony and call centre solution on Interoute VDC, leveraging the throughput, flexibility and scalability provided by this cloud platform. The BQ solution supports its 1,000 employees across different international offices, using Interoute VDC to provide the global reach they need. The solution is complemented with telephony services and worldwide DDIs from Interoute with great cost savings thanks to the economies of scale provided by Interoute's global infrastructure. Since it was founded in Spain, BQ has grown its business inside and outside the country thanks to its latest generation technology devices catalogue and highly competitive prices, as well as its full commitment to its users through a comprehensive support service. Mario Fernández, IT Manager at BQ, has said: "One of the main BQ objectives is to give the best user support. So, we chose Interoute to provide and guarantee the performance of our telephony service. The VoIP solution provided by Interoute meets all our needs: hosted private cloud, high availability and the ability to quickly scale and expand when needed." Interoute Virtual Data Centre is Interoute's scalable, fully automated Infrastructure as a Service (IaaS) solution. Interoute VDC provides on-demand computing, storage and applications integrated into the heart of its customers' IT infrastructure. This networked cloud replaces the need to buy, manage and maintain physical IT infrastructure and is built into Interoute's fibre connected physical Data Centres world-wide. It's simple to provision, scalable, compliant and cost effective. Diego Matas, General Manager at Interoute Iberia, has added: "We are proud that a Spanish company such as BQ, committed to education and pioneering innovation in exciting fields like robotics and 3D printing, has chosen our cloud platform for its networked communications. Interoute's networked cloud will enable BQ to continue to build upon its excellent reputation for high quality service. We look forward to working with this innovative company to support its future ICT needs."

- Now available with limited-time pricing, package brings together InfinityQS’ cloud-based enterprise quality hub, ProFicient on Demand, with training and ongoing services to ensure a successful deployment - InfinityQS International, Inc., the global authority on real-time quality and Manufacturing Intelligence, announces the launch of ProFicient Now!, a program that blends InfinityQS’ cloud-based enterprise quality hub, ProFicient on Demand, with training and ongoing services to ensure a successful deployment. Available with limited-time pricing, ProFicient Now! aims to give manufacturers the knowledge, tools and continued guidance needed to realise the benefits of a cloud-based quality management program and quickly gain a competitive advantage. “In today’s fast-paced market, manufacturers are looking for ways to better align their quality systems with overall manufacturing excellence goals,” said Doug Fair, Chief Operating Officer, InfinityQS. “By combining the power of the cloud with ongoing expert guidance from our engineering team, ProFicient Now! helps both new and existing clients track towards their goals and achieve a competitive edge through their quality initiatives.” With ProFicient Now!, manufacturers receive expert engineering guidance that leads them through their deployment. Included in the ProFicient Now! package is: Training: Administrators obtain comprehensive skills for building and maintaining the system. Solution Design: The client works closely with InfinityQS to examine the current environment and establish goals for the deployment. Onsite Services: An InfinityQS engineer creates the initial system configurations. Quarterly Consultations: InfinityQS experts guide clients in data analysis and help uncover opportunities for improvement and cost reduction. Executive Review: The InfinityQS engineer leads a review with the client senior management team to review successes, quality enhancements and opportunities for improvement that were uncovered during the use of ProFicient Now! InfinityQS ProFicient is a proven enterprise quality hub powered by a robust, centralised Statistical Process Control (SPC) software engine. ProFicient enables global manufacturers to proactively monitor, analyse and report on Manufacturing Intelligence to improve quality, decrease costs and make smarter business decisions. With a cloud-based deployment option, ProFicient streamlines global data collection and analysis with a unified data archive. For more information about ProFicient Now, including its limited-time pricing, visit here: http://www.infinityqs.com/ProFicient-Now-EMEA

Last week’s Gartner IT Operations Strategies & Solutions Summit in Orlando, Fla., was exactly what you’d expect—a place to talk about the IT operations issues impacting some of the largest companies in the world. Even so, there were a few interesting surprises. Among them: 1. Bi-modal is big. Not everyone will succeed. Gartner continued to tell its customers to employ two modes of IT—a traditional, slower moving capability for older, typically internal systems of record; and a high-speed, experimental one for new, typically customer-facing Web and mobile apps. “This is a time of experimentation and innovation,” said Gartner VP and distinguished analyst Chris Howard in his opening keynote. Organizations can’t ignore that there are multiple speeds and they should participate in all. Gartner managing VPRonni Colville added that by 2017, 75% of IT orgs will have this “bi-modal” IT capability. See also: Bi-Modal IT: Gartner Endorses Both Disruptive and Conservative Approaches to Technology However, “50% will make a mess of it,” Colville said. Why? Not necessarily because of technology failings, but more often because of a lack of people skills. 2. IT success is all about people. Donna Scott, also a Gartner VP and distinguished analyst, told her keynote audience that “you will be judged on agility, speed, and innovation.” However, the biggest problems Gartner sees for infrastructure and operations team engagement and innovation are lack of time, company culture that’s not conducive to these approaches, and a lack of business skills in IT. More than half of the people responding to an in-room poll said “people” are the part of IT ops that must change first. Not technology. Gartner research director George Spafford underscored similar issues in large organizations trying to use DevOps at scale: people and “human factors” are the biggest concerns from his in-room poll. All these probably contributed to hiring best-selling author Daniel Pink as a keynote speaker on the opening day of the conference. His focus? Not IT or architecture. Instead, he pounded home the importance of influencing people and selling internally. 3. Big orgs are trying DevOps. But the issues are different at scale. In numerous sessions I saw many hands go up when analysts asked, “Who here is trying DevOps?” Clearly, the approach is getting traction in large companies. But there’s lots of learning still to do. In fact, that was Spafford’s biggest bit of advice. “Always be learning,” he said, “trying to see what works and what breaks, especially at scale.” And, even once you’ve had some initial success, keep learning. “If you’ve done ‪DevOps, stay humble,” he advised. 4. Looking to innovative organizations for ideas … analytics on the rise. Many sessions addressed how large organizations are taking on ideas fostered by smaller, more risk-tolerant companies, and offered advice for doing so successfully. In addition to multiple discussions of DevOps, an entire session was devoted to establishing your own “Genius Bar®—a “walk-up IT support center” as explained in this CIO article. As at previous conferences, Gartner research VP Cameron Haight ran several sessions on lessons learned from firms running massive, Web-scale IT systems. “You need lots of data … and access to it inexpensively,” he said. Some commercial monitoring companies (New Relic included!) got a shout out for taking the lessons of Web scale IT to heart in their offerings. In addition, Haight said, “Analytics are increasingly important for application performance monitoring given the huge amount of data now available.” 5. Cloud: Enterprises want it, but aren’t very good at it yet. Gartner research director Dennis Smith talked through the enterprise’s interest in cloud computing. A huge majority of his in-room poll wanted some mix of both public and private cloud, while only 9% wanted to use only a private cloud environment and a measly 4% were looking to move entirely to the public cloud. The most popular choice (41%) was an 80/20 split between private and public cloud infrastructure. “Enterprises don’t make the dean’s list,” for cloud usage, Smith said, earning no more than a C average in his opinion. Large organizations are doing well at visibility, governance, and delivering standardized stacks, he said, but are less skilled at optimizing for these new environments. Still, Smith said the trends point toward enterprises improving on all fronts. 6. Cloud security can be better than yours. Importantly, Gartner VP and distinguished analyst Neil MacDonald gave the cloud a vote of confidence: noting that, for a variety of reasons, “Well-managed public cloud can be more secure than your own data center.” For example, on-premise software can pose serious security risks, he said, because of “deployment lag” where customers are stuck using software releases with unpatched security vulnerabilities. With a cloud-based Software-as-a-Service (SaaS), security updates can be more quickly rolled out to all customers. But cloud security can be different, requiring a shift to information-level security from OS-level security. Best practices include doing away with a huge pool of all-powerful sysadmins in favor of JEA, or “just enough administration,” where sysadmins have just enough privileges to do their job, and no more. An analogous security practice for compute resources is “least privilege,” where apps and microservices can’t talk to each other unless they specifically need to do so. Audience polling supported MacDonald’s optimistic view of cloud security, which suggests that large enterprises may struggle less with their cloud policies moving forward. 7. Containers: Try ’em! Ahead of this week’s DockerCon in San Francisco, Gartner devoted significant airtime to educating the audience on containers and microservices. My summary of ‪Gartner VP and distinguished analyst Tom Bittman’s advice on containers was simple: Try ’em. Now. Complement them with VMs. ‪And Docker (the company) is important, but not the be-all and end-all in this space. Bittman (copping to some deja vu from Gartner presentations he made on server virtualization 13 years ago) noted that while virtualization has been focused on admin and ops functions, containers are focused on value for developers. But because containers are well suited for driving up VM utilization for workloads that share the same OS, we can expect to see more combinations of containers and server virtualization. Finally, Bittman underscored that Gartner doesn’t see containers having much impact on premise, but making a huge difference in the cloud. That doesn’t necessarily fit with what’s been shown in other research, such as this 2015 State of Containers Survey sponsored by VMblog.com and StackEngine, so we’ll want to watch how this plays out. This is all a lot to digest. The Gartner IT Operations Strategies & Solutions Summitacknowledges the importance of dealing with existing IT systems and practices as well as promising new technologies and thinking, and tries to point a way forward. In fact, Haight had a very good quote about microservices that I thought also served to wrap up the entire event: “If you want to run with the big dogs, you need to rethink application architecture,” he said. That can be very difficult for an enterprise to fully implement … but also very appealing. Note: Al Sargent contributed to this post. All product and company names herein may be trademarks of their registered owners. Server, tortoise and hare, business team, and cloud security images courtesy ofShutterstock.com.

Originally written by David Brimley. The Death Spiral. A new feature in the 3.5 release of Hazelcast is the Cluster Quorum. In this instance we’re not talking about a Quorum in its traditional distributed systems sense, think of a Cluster Quorum as a kind of gatekeeper, protecting your cluster during times of unexpected member loss. You can use Cluster Quorums to restrict operations on Maps or indeed the entire cluster based upon environmental criteria. This sounds great you say, but I’m still not sure how this can help me? OK. Let's take a look at a scenario… Imagine a cluster that has a very high number of writes to a certain map. We also have other maps that are not updated quite so frequently and all the while we have hundreds of clients all reading from the cluster but not at the same frequency as the data that is entering the system. In normal circumstances if a machine or a number of machines were to die in the cluster we may still have enough memory available to store our data, but the amount of threads available to process requests would be reduced. We now have less cores available and the partition threads in the cluster could quickly become overwhelmed by the one map that is updated rapidly. This could mean other clients becoming starved of threads, unable to service requests. It’s also possible that the remaining members would become so consumed that they’re unable to respond to membership pings, the knock on effect could result in the member being forced out of the cluster on the assumption that it is dead. To protect the rest of the cluster in the event of member loss we need a way to stop the writes to the high frequency map whilst allowing operations to the other data structures. We can then continue to provide a good service to our other users whilst the crashed machines are restored to the cluster. Bring on the Quorum! As of Hazelcast 3.5 we now have the ability to restrict operations on distinct data structures. We do this via a Quorum configuration. We observed that other IMDG products provide Quorums that have protection at a cluster level,we decided to go one step further and provide Quorum protection around data structures as well. In the example below we create a very simple Quorum on the default map. The ‘default’ map in Hazelcast is the configuration used if no other match is found. In this instance no operations will be allowed unless the cluster has a minimum of 3 members. You’ll also note that the Quorum configuration is separate from the Map. This means that you can have multiple Quorums in a cluster attached to many different structures. If the Quorum thresholds are not satisfied then a QuorumException is thrown when we try to interact with the default map in any way. Be it from a client or another member. 3 quorumRuleWithThreeNodes Quorum Functions It’s simple to set up a Quorum check based on cluster size as we’ve seen above, but if you want to make a slightly more complex check you can do this by applying a Quorum Function. QuorumConfig quorumConfig = new QuorumConfig(); quorumConfig.setName("MyQuorum"); quorumConfig.setEnabled(true); quorumConfig.setType(QuorumType.WRITE); quorumConfig.setQuorumFunctionImplementation(new QuorumFunction() { @Override public boolean apply(Collection members) { return (members.size() >= 3) && (someOtherExternalClusterState); } }); In the example above we use Configuration API to set-up the Quorum to disallowwrites if the boolean returned from the QuorumFunction is false. In the function we test if the size of the cluster is greater than 3 and also if a variable namedsomeOtherExternalClusterState is equal true. You now get the idea that by using a function you can test for other state and not just cluster member. Listen In. Another nice feature of Quorums is the ability to listen in to Quorum Events. You can register a new callback interface called not surprisingly a QuorumListener. Quorum listeners are local to the node that they are registered, so they receive only events occurred on that local node. 3 com.company.quorum.ThreeNodeQuorumListener quorumRuleWithThreeNodes The QuorumListener has just one method that is called passing you aQuorumEvent. package com.hazelcast.quorum; import java.util.EventListener; /** * Listener to get notified when a quorum state is changed */ public interface QuorumListener extends EventListener { /** * Called when quorum presence state is changed. * * @param quorumEvent provides information about quorum presence and current member list. */ void onChange(QuorumEvent quorumEvent); } The QuorumEvent itself allows you to determine if a Quorum has been established or if it has been lost via its isPresent() method call. Additionally it provides the required cluster members to form a quorum and also the current membership list. Query the Quorums. Above we saw how we could receive callbacks, but in some cases we may just wish to make an immediate check to see if the Quorum is established or not. We can do this via the QuorumService. HazelcastInstance hazelcastInstance = Hazelcast.newHazelcastInstance(config); QuorumService quorumService = hazelcastInstance.getQuorumService(); Quorum quorum = quorumService.getQuorum(quorumName); boolean quorumPresence = quorum.isPresent(); In Conclusion The Cluster Quorum feature is another important tool for you to manage your cluster. In future versions of Hazelcast there are plans to add other data structures, for example you’ll be able to protect operations against Topics or Queues.

[This article was written by Andrew Marshall] We’ve been talking a lot about Docker over the past few weeks—with good reason. Docker’s explosive growth in popularity within the enterprise has enabled new distributed application architectures and with it a need for app-centric monitoring of your Docker containers within the context of the rest of your infrastructure. We’re thrilled to announce today that New Relic’s Docker monitoring is now generally available to New Relic customers, just in time for DockerCon 2015! (And as we noted last week, New Relic’s Docker monitoring solution has been selected by Docker for its Ecosystem Technology Partner program as a proven container monitoring solution.) Why app-centric monitoring? If you’re a software business using Docker containers, chances are you’ve done so to gain efficiencies from your system resources or portability across environments to shorten the cycle between writing and running code. Either way, adding Docker containers to your app development meant a new tier of infrastructure to monitor, which equated to a “black box” in your data—one that you had no visibility into from a monitoring perspective, Docker monitoring with New Relic is designed to “fix” this lack of monitoring visibility by adding an app-centric view of Docker containers to the existing New Relic Servers interface you already use. Now, instead of having a gap between the application and server monitoring views, we’ve added the ability to see containers with the same “first-class“ experience as you would with virtual machines and servers. You can now drill down from the application (which is really what you care about) to the individual Docker container, and then to the physical server. No more blind spots! As we strive to do with all of our products, we took the approach of “important” over “impressive” when it comes to the container information we provide to users. Based on direct feedback from customers, we’ve tried to take the mystery out of finding the right container to help you get back to developing your applications. As the way people use containers changes over time, we plan to continue to listen to our customers to help shape how we approach Docker container monitoring. Restoring 360-degree view of your application environment One example of how app-centric monitoring can impact a team moving to microservices or distributed application environments is Motus, a mobile workforce management company. Motus has been a New Relic customer for more than four years and recently has been shifting to a microservices architecture with approximately 95% of its production workload now running in Docker containers. While Docker helpd Motus gain speed and agility while reducing infrastructure complexity, the link between the application and what was happening with the container it was running on was broken. During the trial of New Relic’s Docker monitoring, Motus was able to more easily identify which container an app was running on, all the way down to the node. That was a big help when they needed to investigate an issue and determine if a new container was required.. During the beta alone, Motus estimates that using New Relic helped them to reduce the time to investigate and fix problems with its Docker containers by 30%! Motus isn’t just using New Relic to diagnose when a problem occurs. Docker monitoring with New Relic has helped Motus analyze and “right size” its containers for the application to better allocate resources for performance and budget. Get started with New Relic’s Docker monitoring today, for more information, please stop by our booth at DockerCon, June 22-23 in San Francisco! Resources: Motus Docker Monitoring Case Study Docker Monitoring with New Relic Enabling Docker Monitoring with New Relic Docker in the New Relic Community Forum

Written by Stephane Combaudon. A question I often hear when customers want to set up a production PXC cluster is: “How many nodes should we use?” Three nodes is the most common deployment, but when are more nodes needed? They also ask: “Do we always need to use an even number of nodes?” This is what we’ll clarify in this post. This is all about quorum I explained in a previous post that a quorum vote is held each time one node becomes unreachable. With this vote, the remaining nodes will estimate whether it is safe to keep on serving queries. If quorum is not reached, all remaining nodes will set themselves in a state where they cannot process any query (even reads). To get the right size for you cluster, the only question you should answer is: how many nodes can simultaneously fail while leaving the cluster operational? If the answer is 1 node, then you need 3 nodes: when 1 node fails, the two remaining nodes have quorum. If the answer is 2 nodes, then you need 5 nodes. If the answer is 3 nodes, then you need 7 nodes. And so on and so forth. Remember that group communication is not free, so the more nodes in the cluster, the more expensive group communication will be. That’s why it would be a bad idea to have a cluster with 15 nodes for instance. In general we recommend that you talk to us if you think you need more than 10 nodes. What about an even number of nodes? The recommendation above always specifies odd number of nodes, so is there anything bad with an even number of nodes? Let’s take a 4-node cluster and see what happens if nodes fail: If 1 node fails, 3 nodes are remaining: they have quorum. If 2 nodes fail, 2 nodes are remaining: they no longer have quorum (remember 50% is NOT quorum). Conclusion: availability of a 4-node cluster is no better than the availability of a 3-node cluster, so why bother with a 4th node? The next question is: is a 4-node cluster less available than a 3-node cluster? Many people think so, specifically after reading this sentence from the manual: Clusters that have an even number of nodes risk split-brain conditions. Many people read this as “as soon as one node fails, this is a split-brain condition and the whole cluster stop working”. This is not correct! In a 4-node cluster, you can lose 1 node without any problem, exactly like in a 3-node cluster. This is not better but not worse. By the way the manual is not wrong! The sentence makes sense with its context. There could actually reasons why you might want to have an even number of nodes, but we will discuss that topic in the next section. Quorum with multiple data centers To provide more availability, spreading nodes in several datacenters is a common practice: if power fails in one DC, nodes are available elsewhere. The typical implementation is 3 nodes in 2 DCs: Notice that while this setup can handle any single node failure, it can’t handle all single DC failures: if we lose DC1, 2 nodes leave the cluster and the remaining node has not quorum. You can try with 4, 5 or any number of nodes and it will be easy to convince yourself that in all cases, losing one DC can make the whole cluster stop operating. If you want to be resilient to a single DC failure, you must have 3 DCs, for instance like this: Other considerations Sometimes other factors will make you choose a higher number of nodes. For instance, look at these requirements: All traffic is directed to a single node. The application should be able to fail over to another node in the same datacenter if possible. The cluster must keep operating even if one datacenter fails. The following architecture is an option (and yes, it has an even number of nodes!): Conclusion Regarding availability, it is easy to estimate the number of nodes you need for your PXC cluster. But node failures are not the only aspect to consider: Resilience to a datacenter failure can, for instance, influence the number of nodes you will be using.

This week we're in Boston at DevNation, an awesome, young (second ever), and relatively intimate (~500 attendees) conference on anything and everything hard-core, cool-and-hot (DevOps, big data, Angular, IoT, you name it), and of course -- since the conference is organized by Red Hat -- totally open-source. So far I've had in-depth conversations with five super-amazing engineers, attended several inspiring keynotes, and chatted with one skilled developer after another. We'll transcribe the deeper interviews shortly, including some on topics totally unrelated to this post. But meanwhile I'd like to offer some thoughts inspired by the first day of the event. The general theme is: we're just beginning to get serious about separation of concerns. The metaphor that keeps popping into my head comes from the first keynote: machines have finally grown up. Imperatives: telling really unintelligent agents what to do (and then they sort of do whatever they please) It is trivial to observe that computers are incredibly stupid. Turing's fundamental paper is about how to figure out whether a theoretical computer will keep calculating the values of a function until the heat death of the universe (okay that's a slight oversimplification). The fact that Edsger Dijkstra felt the need to rail gently against all goto statements in any higher-level language than machine code suggests that, in 1968, far too many computers needed instructions about how to read the instructions that tell them what to do in the first place. Richard Feynman's famous lecture on computer heuristics is the condescension of the man who conceived quantum computing to the level of functional composition (hmmm) and file systems (double sigh). Stupid agents need to be told exactly what to do. Then they need to be told to pay attention to the exact part of the command that tells them exactly what they have been told to do (dude, just goto line 1343 already and shut up). Then they don't do what you told them (optimistically we call this an 'exception'), and then you send them into time out / set a break point and try to figure out where the idiot state muted off the rails. They stare blankly at the wall / variable / register and either do nothing or repeat another unintelligibly wrong result until you notice that your increment is (apparently meaninglessly to you) one bracket too deep. You sigh and tell them what to do again, and after a while they hit age thirty (life-years/debug-hours) and maybe do something useful with their (process-)lives. Well, maybe I'm straining the metaphor a little here, but you get the point because it cuts too close to home. We spend far too much time fixing stupid mistakes that we didn't even know we were making because -- like all actual human beings -- we assumed that the agent we commanded will use their common sense to iron out those few whiffs of, admit it, frank nonsense that our step-by-step instructions will probably always contain. So, at least, goes the imperative programming paradigm. The machine does what you tell it to; and the universe collapses onto itself before the last real number is computed. Functions: reliable, predictable adults Time to give credit where it's due: I'm really just riffing on the metaphor Venkat Subramanian offered in his highly enjoyable keynote on The Joy of Functional Programming yesterday morning His not-so-smart agents -- the 'programmed' of imperative programming -- were toddlers. Since I don't have any kids, I can't presume to understand this experience fully (although I did grow up with three younger brothers..). But the general idea is: imperative programming is tricky because, when you spell everything out super literally, it's very hard to tell exactly why what you thought should happen didn't. Venkat's talk was a whirlwind of functional concepts, from the thrill of immutability to the self-evident utility of memoization. For random (Myers-Briggs?) reasons, the object-oriented paradigm never seemed very intuitive to me -- I've gravitated towards functional style even when the problem domain wasn't actually modeled very well by functions -- but Venkat's side-by-side implementations of simple calculations in OO and functional Java showed the readability delta very clearly. Functional code is beautiful because it looks like its purpose. It tells you flat-out: here is what I do; and then it does it. But immutable functions are also beautiful because they do exactly the same thing every time. I couldn't count on my two year old brother very much at all because given a certain input I had pretty much no idea what would come out. But we all count on our grown-up collaborators to output exactly what they should, given a definite input, predictably and reliably every time. Of course, people also do more than expected -- every intervention of intelligence is an injection of creativity, not generated by the definition of the function -- but at least they do what you need them to do and no less. Containers: grown-ups with good boundaries I'm picking out just one aspect of the resurgent 'joy' of functional programming because the renaissance of containerization (another 'old' technology that is just now really taking off) is, I think, a part of the same shift toward, let's say, treating computers as adults. If functions are reliable agents, then applications in well-defined containers are self-sufficient agents who know exactly what they need from others and neither require nor demand anything more. If apps on dedicated VMs are teenagers negotiating personal boundaries by waking/booting up independently (and taking far too long -- and far too many resources -- to do so, given their meager output) -- or bubble boys, isolated in ways that are unfortunate in order to isolate in ways that are absolutely necessary -- then containerized applications are subway-riders who jam into the train without offending anyone or campers who can live anywhere with just a backpack of just the stuff they need. Of course, subway-riders and campers do more than just not-mess-up. But what's kind of neat about containers is that -- like an adult with good boundaries -- clearly defined bounds and interfaces free up the application / mind to do whatever world-changing thing the developer / human has cooked up. I'll come back to this metaphor in a later article. (Mesh networks, SDN, and ad-hoc computing are all part of the same picture, I think. Kubernetes probably is too, along with event-driven and reactive programming, the actor model, dreams of Smalltalk, and of course REST, at least of the HATEOAS flavor.) But maybe this isn't a good way to think about some of these recent sparks in devworld within a single paradigm -- and maybe my perpetual discomfort with OO is influencing me too much. What do you think?

[This article was written by Kevin Casey] Welcome to This Week in Modern Software, orTWiMS, New Relic’s weekly roundup of the need-to-know news, stories, and events of interest surrounding software analytics, cloud computing, application monitoring, development methodologies, programming languages, and the myriad of other issues that influence modern software. This week, our top story goes inside President Obama’s secret team of tech geeks, 140 of them and counting: TWiMS Top Story: Inside Obama’s Stealth Startup—Fast Company What it’s about:If the President of the United States walked into the room and personally recruited you to rebuild the country’s technology infrastructure, could you turn him down? He’s serious, and that room is theRoosevelt Room in the West Wing of the White House, by the way. AsLisa Gelobtersays: “What are you going to say that?” Gelobter’s answer was “Yes”—she’s now chief digital officer for the US Department of Education, part of a 140-person-and-counting tech team that’s functioning something like an elite startup embedded inside the federal government. Its business? Only modernizing the technical infrastructure, applications, and processes of just about every federal agency. Why you should care:What was once something of a tech desert—the federal government—is beginning to draw top private-sector talent inside the Beltway. The team, led by Mikey Dickerson (who helped lead the team that rescuedHealthcare.gov) andformer US CTO Todd Park, also includes the likes of former Googler Matthew Weaver, and it hopes to hit 500 people by the end 2016, shortly before President Obama will leave office. Its challenges are immense, from tackling government bureaucracy (to test just how entrenched the suits were, Weaver requested the official title “Rogue Leader”—and he got it) to the fact that its recruiting pitch includes the phrase: “You’ll have to take a pay cut.” But its mission is both noble and necessary, and the appeal of working on major problems with enormous public impacts appears to be working. Recommended reading. Further reading: Mikey Dickerson’s 10 Tips for Dealing with Bureaucracy—New Relic Blog [Video] Airbnb Open Sources Software to Lure Talent Amid ‘Insane’ Competition—CIO Journal What it’s about:Airbnb added three new apps to its open source portfolio earlier this month, but the motivation wasn’t just trying to give employees the best business tools or contribute to the software community at large. Sure, that might have been part of the equation, but the rental booking site hopes open-sourcing some of its toolkit will help recruit the best software talent in the face of what director of engineeringMike Curtiscalls “insane” competition in the Silicon Valley labor market. Why you should care:In the software arms race, any little edge counts. Curtis tellsCIO Journalthat Airbnb will keep the proprietary stuff closely guarded, of course. But it will open source “generic” tools with wider industry use cases, such as its recently releasedAerosolvemachine-learning package and itsAirpalcloud-based data querying tool. The latter, which works with Facebook’s open sourcePrestoDB, aims to simplify SQL queries to the point where you don’t need to be a big data wonk or business intelligence guru to run it. Indeed, one in three Airbnb employees have run a query on it in the year since it launched. Airbnb has contributed a dozen open source tools on its aptly namedNerds site(gotta love that!) to date, something the company hopes both contributes to greater good but also advertises its software innovation to potential hires. Google Is Wielding Its Own Secret Weapon in the Cloud—The New York Times What it’s about:In thecutthroat competitionfor public cloud business, Google may be its own best customer testimonial. In advance of this week’sOpen Network Summit, theTimes’Bits bloglooked at Google’s plan to not only unveil cloud customers such as HTC but reveal much more than ever before about its own infrastructure. Google did just that on Wednesday, offering a look inside itsdata center networking, including its massive-capacity, lightning-fast Jupiter network. Why you should care:As major cloud players continue to zap prices with their shrink-rays, it’s increasingly clear that features and underlying platforms will distinguish one from the other when enterprise users make their pick. Google is taking a big step toward writing its own story in this regard, and the synopsis might read something like: “We’re pretty good at this stuff.” Its Jupiter fabrics deliver 1 petabit per second of bisection bandwidth, according to Google, or “enough for 100,000 servers to exchange information at 10Gb/s each, enough to read the entire scanned contents of the Library of Congress in less than 1/10th of a second.” If it sounds like a bit of bragging, well, yeah—it is. But it’s bragging with a purpose: Attracting devs who want access to the same technology without having to build it themselves.Google’s Amin Vahdat connected the dots in a blog post: “The same networks that power all of Google’s internal infrastructure and services also power Google Cloud Platform.” Move Over, Meeker: Byron Deeter’s State of the Cloud Report—Bessemer Venture Partners What it’s about:With a nod to Mary Meeker’s classicState of the Internet report,Bessemer Venture Partners’Byron Deeterchecks in with his 2015 State of the Cloud Report. Given cloud computing’s relative youth and rampant ascension, it’s no surprise the stats are staggering. Here’s one to start: Cloud revenues have increased tenfold in the last six years, from a scant $5.6 billion in 2008 to more than $56 billion in 2014. And it’s going to double again in the next four years, according to BVP’s projections, to $127.5 billion in 2018. Why you should care:Deeter’s full presentation is worth a weekend watch or read, but it’s the forward-looking slides that may be most compelling for software pros. Deeter notes both the immense risks and opportunities in cloud security, unveiling a 10-point security plan for cloud startups on slide 37. To underscore the security landscape, Deeter quotes an unnamed cloud CEO who says aDDoSattack that took down the firm’s API caused more customer churn in one day than in the rest of its history. Wow. He also addresses the exploding market for cloud services built specifically for developers including, yes, New Relic. And for mobile developers, slide 44 underscores something we’ve talked about before in this space:the real money’s in enterprise apps, and it’s still a largely untapped market. Click through thefull slide deck hereorwatch video of Deeter’s presentation here. Bandwidth: The Next Frontier of Cloud Computing—ZDnet What it’s about:Is networking the next big thing in the everything-as-a-service age? It just might be, as firms likePacnetvie to deliver networking capacity on a pay-for-what-you-use model that some industry folks say better suits cloud environments facing significant but uneven networking needs. Why you should care:As author Drew Turney notes, there’s a common blind spot when it comes to cloud computing’s many shapes and sizes: Moving all that data from points A to Z, and everywhere in between, which can cause both performance problems and undue financial pressures. The promise of Networking-as-a-Service (NaaS), industry execs tell Turney, is that it can provide more efficient, scalable networking for short-term usage bursts such as customer traffic spikes or large cloud backup-and-storage jobs, enabling companies to later dial down their capacity as needed. Combined withSoftware-Defined Networking (SDN),NaaS makes it possible to build intelligent applications that manage their own networking needs, which might be the most significant enterprise potential of NaaS, saysNuage NetworksarchitectMarten Hauville. Page Bloat: Average Web Page Now More Than 2MB—The Performance Beacon (SOASTA) What it’s about:Do you need to put your website on a diet? Apparently so: The average Web page topped 2 MB as of May 2015, according to ongoing tracking atThe Performance Beacon. That’s double the average page weight from just three years ago. The site projects average page weight will exceed 3 MB in late 2017. Why you should care:Performance, performance, performance:Slow speedsare a killerin the modern software era. While author andSOASTAUX evangelistTammy Evertsrightly notes that page weight is not the only factor in Web optimization, we’re simply not paying it enough attention when designing and building Web pages. Images are the big culprit in the Web’s expanding waistline: they comprise nearly two-thirds of the average page’s weight, and video is a growing part of our Web diet, too. But other factors such as custom fonts play a role, adding weight even as the Web sheds previous performance hogs like Flash. The ideal weight? 1 MB, she says, which will save crucial seconds in load times. Sounds like it’s time to hit the virtual treadmill.

Last month we shared the news about the debut Opsmatic and their live state monitoring service, a solution that delivers a precise, real-time picture of the detailed configuration – as well as changes that affect a computing infrastructure. We wanted to let you know that Opsmatic continues to expand its service capabilities with the announcement of two new versions. The Enterprise version of the Opsmatic service includes all the features we discussed last month in their Professional edition with the addition of single sign-on and dedicated support. The On-Premises edition embodies features contained in the Enterprise version in a solution designed for customers with an isolated infrastructure who require an internally-deployed solution. Details of Opsmatic’s new service offerings are outlined in the press release below. Should you have any questions, Opsmatic would be happy to respond to them.

The complexity of big data makes it a difficult concept for many to grasp, and utilizing it effectively is one of the biggest challenges businesses face today. There is little doubt that big data offers organizations a number of clear advantages, but applying them across the entire enterprise is one obstacle that can truly be described as formidable, even daunting, to even the most technologically savvy companies. One department might be able to create its own business solutions through big data analytics, while another department might come up with answers of their own, but lack of true coordination and collaboration remains a significant problem. Businesses aren’t without help in this area, however, because they’ve encountered similar problems before. Many companies have encountered issues such as virtualization technology sprawl, and the lessons learned from addressing that problem could prove to be exceptionally valuable when dealing with big data true cost of ownership (TCO). To understand the problem and the solution, we must first look back at the rapid growth of virtualization technology, more specifically server virtualization. As businesses adopted virtualization, the mainframe systems soon diverged into multiple systems. The more popular virtualization became, the more projects were taken on and the more technologies diverged. Larger companies eventually sought technology specialists to work within their areas of expertise. The result of the use of these individual teams was virtualization technology sprawl, an inefficient development that eventually lead to even higher operational costs. For all the benefits virtualization technology offered, many of them were outweighed by the increased demands and greater management complexity that came from technology sprawl. Businesses were quick to come up with new solutions for the problem. The most common was to adopt a converged infrastructure . This strategy directly addressed the higher operational costs that resulted from technology sprawl, basically breaking through the silos by taking multiple technologies and combining them into single stacks for computing, storage, and networking. This made the management of virtualization technology much easier since operational complexity was significantly reduced. In other words, management of this technology was kept at a reasonable size. The same principle can apply to big data management across an entire organization. When it comes to management of big data and hadoop security, it’s easy to get caught up in the immensity of it all. The fact that big data is so versatile and can be applied to so many different use cases also means it can apply to any number of different divisions within a company. This creates silos and a general desire to hold onto data sets. In other words, big data ends up in a sprawl of its own, becoming that much more unwieldy and complicated, which is a major problem for a technology that’s already so complex to begin with. The lesson that every company should take away from the solution to virtualization technology sprawl is the breaking down of barriers to big data management. It all comes down to ready access to all the necessary data no matter what roles an employee may have within a company. Businesses shouldn’t have to worry over the cost it takes to store and process data since the insights gained from big data analytics are particularly valuable. Most importantly, it’s about avoiding big data from getting too big, to the point where it becomes unmanageable and merely adds to the overall operating costs of a company. It’s true that big data introduces more complexity, but businesses that have learned how to store and process it efficiently, sometimes through big data platforms or cloud-based services, are in a more advantageous position than companies still dealing with technology sprawl. The lessons learned from previous problems can indeed play a helpful role in solving the problems many experience today.

London, UK – FusionExperience, the business and data solutions provider, today announces the success of its first salesforce.com partnership with Cloud Consulting Ltd. (CCL). CCL was working with an international airline client to migrate a legacy charter and group booking application from one Salesforce.com instance to a new one. Very early on in the project CCL discovered that there were considerable elements of unsupported custom code and that these had to be redesigned and redeveloped. The airline took the opportunity at this stage to request changes and improve the application in line with their new business processes. CCL worked with FusionExperience to migrate the application to the latest salesforce.com environment and re-architected the booking engine functionality and complex pricing algorithms using Apex and VisualForce. For business reasons the airline had a strict project deadline and despite all the unknowns involved the project timescales were maintained and FusionExperience delivered on time and to budget. The airline went live with the application on schedule without any post-production problems or warranty fixes required. They now have an up to date system that has achieved a game changing transformation in the way it does business. Robin James, Platform Evangelist for FusionExperience said; “The ability to seamlessly work with our partners on salesforce.com projects enables rapid scaling of resources and capabilities. This ensures that the client is delighted by the results, yet unaware of the complex extended ecosystem that has been involved. This is facilitated by that fact that we all speak the same salesforce.com language. Cloud Consulting is an ideal partner to work with in this way, as our delivery and technical strengths are well matched with their intimate client facing approach.” Tim Pullen, Managing Director of CCL added: “We already had a close relationship with FusionExperience and it was natural for us to turn to them for help with this suddenly extremely challenging project. The combination of cleaning, segmenting and splitting the data in Salesforce.com, extracting the system configuration and custom code and then creating a new system was tough enough to start but then having to redevelop the application from scratch took it to a new level. Right from the start Robin James and his team took everything in their stride and provided a level of comfort, reassurance, skill and professionalism that we’d never experienced before from other partners. Bear in mind that the old system had no user or technical documentation plus undocumented code and you begin to understand just how good the end result has been for the airline. Thank you Fusion!”

From the DevNation Agenda site: You've probably heard a lot about Linux containers and the exciting potential they hold. In this presentation, Matt Hicks will cover how Docker and Kubernetes have evolved to fundamentally change how you will approach development and operations. If you are looking for an understanding of the technology and how it relates to the common roles in IT today, this is the talk to watch. Speaker: Matt Hicks -- Vice President of engineering, Red Hat Matt Hicks is a founding member of the OpenShift by Red Hat team. He has spent more than a decade in software engineering, with a variety of roles in development, operations, architecture, and management. His real expertise is in bridging the gap between developing code and actually running it in production. An expert in IT and cloud-based architectures, he spends his time these days evolving OpenShift to use the power of cloud and make developers more productive.