Lambda Monitoring Just Got Easier Thanks to These 3 Tools
Lambda monitoring just got a whole lot easier. Check out this post where we explore the top three tools for lambda monitoring.
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Now, when we already know what AWS Lambda is and how to use it, we should mention some more advanced tactics to obtain as much experience and knowledge about AWS Lambda as possible. What would you do in case you stumble upon an error inside your AWS Lambda function? Should you ask a more experienced colleague to solve that issue for you or do you use Google to try and find the solution yourself? Leaving it unresolved is out of the question. How about using tools that can handle and solve AWS Lambda errors?
Well, of course, they exist. Someone before you already had their share of headaches regarding this problem, and they’ve found a way to build tools that will manage and solve these errors and issues for you. In this article, we’ll mention the top three tools that solve AWS Lambda errors.
Dashbird, for example, has the ability to detect all and any failures for any programming language you use, like Node.js, Python, and Java. This includes timeouts, early exits, crashes, and configuration errors unique to serverless. Dashbird offers full account overview with real-time metrics and system health included. You can gain insight into invocation volumes, billed duration, errors, alerts, resource usage, and much more, and it's all in one place. Stack tracing is yet another help that Dashbird offers so that you can troubleshoot errors quickly with little hassle.
Dashbird’s alert system is also made to your comfort. Whenever something happens or breaks, you’ll be notified either via your E-mail, Slack, or even both, if needed. Dashbird will provide instant metrics regarding errors, duration, invocation, code execution, and memory usage. To be able to analyze invocations with log and runtime data, you should get the needed observability. There are much more offerings from Dashbird, and you can see them all if you visit Dashbird’s product page.
Raygun is another excellent error handling tool for AWS Lambda that is quite simple to integrate. Raygun allows you to record software errors, which give you the advantage because you will be able to fix the errors as soon as they appear. Raygun doesn’t give you the direct access to system resources, so your only option for storing error logs is by using a cloud provider. Raygun’s cloud offering is utilized for software errors tracking directly with Lambda. If anything goes wrong with your code, Raygun will immediately analyze what happened and send all the details to a hosted service. Raygun will notify you as well in real-time about which error gives you the opportunity to resolve the issue. When it comes to fees and costs, Raygun is one of a kind.
We already know that AWS charges on request count and compute time, but the best part is that when Raygun is initialized, it’s a single attached line of code that’s listening for unhandled errors. All of these facts mean that Raygun has a zero impact on the costs. In case that you are generating errors where Raygun must collect information, it can send them off, and it might make some additional charges to your account. All in all, AWS Lambda and Raygun will provide you with a tremendous serverless product offering. By using Raygun, you’ll be able to keep costs at bay, and you won’t need to worry about managing infrastructures and servers manually.
Airbrake’s external integrations are HipChat, JIRA, Pivotal, GitHub, and many others. Airbrake also has mobile tracking abilities with Android and iOS support. There are also not so many fun facts regarding the Airbrake. You should know that Airbrake is quite tricky to set up when compared to other tools in this space. It also has a relatively lousy UI. When it comes to Java, support is only partial since the only support it offers is for Log4j or Logback support, but in case you don’t use Log4j, you’ll need to set up your app to send data directly to Airbrake. Java installation requires to make build changes, and it only works for Maven. The alternative is “manual labor.” Security might be of concern since filtering the personal identification information can be impossible so that it might require manual work from you. When it comes to charges, Airbrake has three packages to offer, which are based on the number of users and number of projects you want. The tiers go from $39, $89, and $109 per month.
Considering you know what your preferences are and which programming languages you use the most, you’ll be able to sort out which tool solves AWS Lambda handling in the way you need. In this article, we’ve mentioned the top three tools, but there are many others!
Feel free to let us know your favorite lambda monitoring tool in the comments section below!
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