Monitoring is often not the first thing on the mind of the modern developer. Yet, it’s necessary at many points of the software development lifecycle, including: before deprecating an API, before launching a new feature, after launching the feature, and more. In fact, monitoring needs can vary much more than the classic Ops monitoring.
The best way to provide full-stack observability across applications, network and infrastructure is by offering a comprehensive partner ecosystem. Here's how to do it.
Are you overspending on monitoring and APM tools? Forrester’s Total Economic Impact analysis of Honeycomb identified significant ROI in customers using us to reduce spend on less efficient APM workflows. But this isn’t about budget reallocation to a newly branded set of similar but shinier tools.
Remember the old days where if you had an uptime of 99.9 you could be fairly confident everyone was having a good experience with your application? That’s not really how it works anymore. Modern, distributed systems are so complex they typically fail unpredictably, making it much harder to diagnose issues. Traditional monitoring grew out of those early days, allowing you to check the health of simpler systems.
Honeycomb uses AWS Lambda as a core part of our query execution architecture; Lambda’s ability to quickly allocate lots of resources and charge us only for use is invaluable to keeping Honeycomb fast and affordable. Our total Lambda bill is easily accessible in the AWS Console, but how do we know which customers or application areas dominate this bill? How do we judge the cost of changes we make to our own software?
Note 8.3.0 has an issue that could cause creating and accessing snapshots against Azure snapshot repositories to fail authenticating when using SAS tokens. This impacts self-managed customers who have deployed 8.3.0. Elastic Cloud Azure deployments are not currently being upgraded to 8.3.0 and are not impacted as a result. Visibility is crucial for ensuring application performance but it can be difficult to efficiently scale monitoring across all your critical infrastructures, platforms, and services.
VMware Tanzu Observability offers easy integration with Amazon Web Services (AWS) CloudTrail, enabling operators to view events that are related to governance, compliance, and operational and risk auditing for your AWS account. This post walks you through the process of integrating CloudTrail Service with Tanzu Observability Wavefront to take advantage of these consolidated features.
I recently attended Sapphire Ventures' Hypergrowth Engineering Summit (thank you David Carter and Sapphire for the invitation! I wrote a separate blog post on the whole thing), and one of the sessions was a panel discussion with Rob Zuber, CTO at CircleCI and Jonathan Nolen, SVP of Engineering and Product at LaunchDarkly. The session was illuminating: they talked about how in this world of everyone shifting left, teams should actually consider shifting right.
“It’s too expensive!” “Do we really need another tool?” “Our APM works just fine.” With strapped tech budgets and an abundance of tooling, it can be hard to justify a new expense—or something new for engineers to learn. Especially when they feel their current tool does the job adequately. But, does it?
Organizations struggle with getting the right visibility into their environments. Better visibility can improve performance, increase uptime (or decrease downtime, depending on your perspective) and ultimately improve customer satisfaction. Finding the right tool, however, can be a real challenge. Making matters even worse, vendors seem to be announcing new observability platforms every day.
When we came across Dotan’s article “Observability Is a Data Analytics Problem” on LinkedIn, he got our full attention. We totally agree with his views on observability and data analytics.
Visual Studio Code (VScode) is an open-source and cross-platform source-code editor. It was ranked the most popular development tool in the Stack Overflow 2021 Developer Survey, with 70% of the respondents using it as their primary editor. VScode allows you to use a few programming languages like JavaScript and TypeScript. Still, you need an extension if you want to use any other programming language and include extra functionalities to improve your code.
Debugging application performance in Azure AppService is something that’s quite difficult using Azure’s built-in services (like Application Insights). Among some of the issues are visualizations, and the time it takes to be able to query data. In this post, we’ll walk through the steps to ingest HTTP Access Logs from Azure AppService into Honeycomb to provide for near real-time analysis Access Logs.
This article was published in The New Stack. For most developers, software development means there is an API for almost everything, hardware is provisioned via the cloud and the core focus is on building only the features most crucial to your business. Of course, all these integrations and modern distributed architectures create their own set of problems. Having full insight into your application has become even more important and is now commonly known as observability.
As organizations look to become cloud-first to meet the growing demands of the shifts in the ways we do business, we have seen the pace of digital transformation accelerate. As a result, organizations have evolved their cloud strategies to multi-cloud environments and are adopting more containers, microservices, and cloud native technologies. This is creating increasingly distributed systems, making it harder to gain a comprehensive view into how they’re performing.
Parsing bugs are the gift that keeps giving in the age of APIs. We use a service; it works perfectly in debugging, QA, etc. Then some user input that made its way to the web request, returns a result we just can’t parse. Unfortunately, there isn’t much we can do at this stage. We need to understand why the failure occurred and how we can workaround it and fix it.
Rapid digital transformation has taken shape in recent years, with a heavy focus on cloud usage. Many firms are shifting workloads to the cloud, upgrading legacy technology, and restructuring business concepts and workflows to reap the countless benefits of becoming a digitally transformed enterprise. However, these adjustments are not without their obstacles. Cloud technology is as technical as it is valuable to a company's commercial objectives.
In the current world, observability is something that no one should ignore. This is because of the ever-increasing services and technologies required by modern enterprises. Observability is about monitoring, logging, tracing, debugging, and profiling similar systems. When you don't monitor your applications, you can't know whether they are working correctly. A well-designed app or system should have the right observability from its development stage.
Back in November 2020 Apple’s M1 chip was introduced and as the end users moved forward to M1 based Macs it became mandatory to build applications that are compatible with the new technology. The M1 chip has incredible improvements and features but I won’t cover them in this post.There are many resources on the internet covering this and I encourage you to explore them. In this post I will cover several challenges I tackled while setting up an M1 build.
Monitoring and observability have increased with software applications moving from monolithic to distributed microservice architectures. While observability and application monitoring share similar definitions, they also have some differences. The purpose of both monitoring and observability is to find issues in an application. However, monitoring aims to capture already known issues and display them on a dashboard to understand their root cause and the time they occurred.
At its core, observability is understanding the internal state of your systems based on the telemetry they output so you can effectively troubleshoot, debug, and tune performance. However, there’s a tendency to reduce observability to a collection of logs, metrics, and traces, which strips away much of the visibility you need to understand what’s going on.
I've never been on call before, and I'm not sure what to expect, or how I can best prepare for it. Will I need to upend my life just in case the pager goes off? And how should I best cope with getting paged? I've read Charity's piece on the opposite problem of wanting to stop being on call, but it didn't quite answer my question.
Many organizations manage applications that are supported by a large number of services in multiple environments, ranging from the cloud to their own data centers across the globe. As these organizations scale and accelerate service adoption, the volume of telemetry data in their environments multiplies every year.
Say you have a new code base to study or picked up an open source project. You might be a seasoned developer for whom this is another project in a packed resume. Alternatively, you might be a junior engineer for whom this is the first “real” project. It doesn’t matter! With completely new source code repositories, we still know nothing… The seasoned senior might have a leg up in finding some things and recognizing patterns.
I can’t believe that OpenObservability Talks podcast is already celebrating its second anniversary. It feels like just yesterday I wrote the summary of the summary of the first year, sharing the hectic times of starting a podcast in the midst of the COVID-19 global pandemic. The pandemic has been with us most of this year too, but it didn’t stop us from bringing the latest on the best of breed open source observability.
I’m Phillip, a product manager here at Honeycomb. After eleven-ish months of working on our product, I totally understand observability, right? ...Kinda? Sorta? Maybe? I'm not sure—but, I have been sitting in this space long enough to be a little better than clueless. Here's my guide on the topic. I hope it helps, especially if you’re passionate about exploring alternative ways you or your team can manage today’s cloud-native applications.
I’m thrilled to announce today that Logz.io has been named a Visionary in the 2022 Gartner® Magic Quadrant™ for Application Performance Monitoring and Observability. Gaining this recognition from these leading industry experts, in my opinion, is an outstanding accomplishment for our entire organization – the product of years of hard work and putting the needs of our 1,300-plus customers first.
We are excited to announce that Elastic has been recognized as a Visionary in the 2022 Gartner Magic Quadrant for APM and Observability for the second year in a row. In addition, the Elastic solution scored among the Top 3 vendors in five out of six use cases in the 2022 Gartner Critical Capabilities for APM and Observability.
Gartner® has published the 2022 Magic Quadrant™ for APM and Observability, an annual report that evaluates vendors in this category. We’re honored that Datadog has been recognized as a “Leader” within this Magic Quadrant report for the second consecutive year, with the highest position for Ability to Execute.
Honeycomb ruffled the first of many feathers nearly seven years ago when we coined the term “observability” in talking about production code. Today, we get to celebrate a major victory in our push for the term to break free from its unsuitable parent category, Application Performance Monitoring (APM).
I use .NET and I keep seeing something called `Activity` but in OpenTelemetry there is only talk about “Span” and “Trace,” why? And what should I be using? This is understandable, and has caused confusion since that decision was made by Microsoft back in 2018/19 (I believe). I’ll do my best to provide some guidance on what the distinction is, and also when each is useful.
Monitoring and analyzing log files to identify and resolve issues make up log observability. Log analytics is the process of extracting insights from log data. Logs are a valuable source of information for IT operations teams, as they provide insight into what is happening on a system or network. Logs can monitor system performance, troubleshoot problems, and identify security incidents. Logs are a vital part of application performance management.
Monitoring is often not the first thing on the mind of the modern developer. Yet, it’s necessary at many points of the software development lifecycle, including: before deprecating an API, before launching a new feature, after launching the feature, and more. In fact, monitoring needs can vary much more than the classic Ops monitoring. My podcast guest Liran Haimovitch is the co-founder and CTO of Rookout, a live data collection and debugging platform.
As the cost of computerization and connectivity continues to plummet, the number of computers, servers, devices, and sensors continues to rapidly proliferate — and they are generating an unfathomable amount of telemetry data. Telemetry data (the metrics, events, logs, and traces being generated by applications and IT infrastructure) is growing so rapidly, it is virtually impossible to quantify.
A couple of weeks ago, we had a great time hosting the workshop you can see below with Vlad Mihalcea. It was loads of fun and I hope to do this again soon! In this workshop we focused on Spring Boot performance but most importantly on Hibernate performance, which is a common issue in production environments. It’s especially hard to track since issues related to data are often hard to perceive when debugging locally.
If there was a question on if an enterprise needed an observability pipeline in 2019 or 2020, we now know the answer is: yes. The observability data management methods of the 2010s aren’t going to work in the 2020s. Data is growing too fast for us to ignore, and the need to gain intelligence from said data continues to grow in importance. Data (and access to it) is becoming a competitive edge for many enterprises today.
Today’s modern applications contain a broad set of microservices, with containers and serverless becoming the architectures of choice for many cloud applications. Both architectures facilitate highly scalable systems, and while which approach to take is routinely debated, containers and serverless technologies are being used in tandem more and more.
What's the first small thing to do in o11y that would teach me something, bring something valuable, and open the way for something else? Observability doesn’t have to be a big, company-wide project. It can be useful locally and individually. A little playing around can get you some crucial insight into how your software works. Try it as a team, or in a pair, or by yourself. It takes 3 steps: Step 1 is easy. The other two might take ten minutes, or maybe more like a day.
When it comes to monitoring and specifically IT Operations Monitoring (ITOM), everyone is saying monitoring is dead – you need observability. Vendors are jumping on the observability bandwagon. There’s a lot of noise about observability, network observability, full-stack observability and every other kind of observability you can imagine. This is a topic we have touched on in the past.
Creating an observability strategy is a lot like playing with Legos: It takes small building blocks to create a bigger picture, but the slightest mistake could throw off an entire build — and often you realize it very late in the process and have to rip and repair the Hogwarts castle infrastructure you spent many days creating.
In March, we announced official support for a Honeycomb Terraform Provider. Today, we’re announcing additional support for managing Honeycomb Service Level Objectives (SLOs) with Terraform. This furthers Honeycomb’s support for configuration as code and it gives you programmatic control for an immensely popular Honeycomb feature.
It has been seven years since Rent the Runway posted their engineering ladder, kicking off a veritable trend of engineering teams open sourcing their ladders. Interestingly, nearly all of them seem to have coalesced around “area of scope” as a useful proxy for level. At first glance, “area of scope” does seem to make sense. Senior engineers should be able to work across larger areas of the organization. In addition, your area of influence should expand as you gain experience.
