Whether you’ve just started your observability journey or haven’t started one at all, Techstrong Research is here to help the industry gain insights into observability with their “Observability at the Speed of Innovation 2022” survey, sponsored by StackState. Techstrong Research, an industry analyst and consulting group focused on the business outcomes of disruptive technologies, is researching where organizations are in their observability journey.

Having joined Grafana Labs as one of our first data & analytics hires, I spent much of my time in the first few months considering how we should structure our data stack to optimize for a quick path to value, while allowing our small data team to scale going forward.

We’re delighted to announce that Lightrun for Web IDEs is now available for our beta users! Lightrun for the Web is now supported in three different IDEs: If you want to check out the individual plugins, check out the respectable documentation articles: Lightrun’s users are now able to connect to their live applications directly from the browser, without having to download one of our dedicated plugins – and enjoy the full suite of Lightrun features right in the browser.

Monitoring is an essential function of enterprise SRE teams and a critical component of business service deliverability. Its importance has only grown as enterprise environments and technologies continue to evolve at a rapid pace. Unfortunately, traditional monitoring is no longer enough.

Monitoring and visibility are dead. If you don’t have Full Stack Observability (FSO) you may as well just pack up and go home. Your business will fail, and you will be unemployed with no hope for the future. At least, that is what vendors currently pitching FSO would have you believe. But what is full-stack observability? Observability is the current buzzword in the monitoring industry, and full-stack observability is what vendors are currently focusing on.

As many of you may have read, Amazon has released C7g instances powered by the highly anticipated AWS Graviton3 Processors. As we shared at re:Invent 2021, we had the chance to take a little sneak peek under the Graviton3 hood to find out what even more performance will mean for Honeycomb and our customers.

“We lost choice and control when we migrated to Splunk Cloud, but got it back when we adopted Cribl Stream.” The above quote is from a new Cribl customer talking about why they adopted Cribl Stream to manage observability and security data.

Dear Miss O11y, I’ve been told I need to use the OpenTelemetry Collector, but I have no idea what it is, or why I need it? Should I be using it? What value does it add? What the hell am I missing?

Efficient use of observability statistics is essential to any microservice architecture. OpenTelemetry is a project supported by the Cloud Native Computing Foundation (CNCF) to enhance the observability of microservice projects. AWS Distro for OpenTelemetry (ADOT) is an AWS-supported distribution of the OpenTelemetry project specifically designed to improve the observability of AWS projects.

Hive smart meters revolutionized the way customers control their energy use. But since their launch in 2012 by UK energy company British Gas, advances in cloud technology and a rapid increase in the number of smart homes has led to an explosion of data.

The telecom industry is at an inflection point today, where the endless possibilities of 5G meet the growing challenges of accelerating 5G monetization. This is particularly true for telecom providers who have pumped billions of dollars in building 5G networks. The telecom cloud market is expected to cross USD 74 billion by 2026.

More often than not, as developers, when we get a report that a large customer is hitting 502 errors, there's a flurry of activity. What's wrong? Is something deeply broken? So you start digging through AWS logs to see what you can find, but it's hard to reproduce. Sometimes, there's no clear answer, and you move on without any resolution. What if I told you it doesn't have to be this way?

New Relic is known for empowering the world’s leading engineering teams to deliver great software performance and reliability. And the network that delivers that service to New Relic’s users plays a critical role. Hiccups in the performance of the network between New Relic’s mission-critical service and their users can create a cascade of problems.

We are excited to share the latest advances around the Deep Learning Toolkit App for Splunk (DLTK). Earlier this year, Splunk’s Machine Learning Toolkit (MLTK) was updated with some important changes. Please refer to the blog post Driving Data Innovation with MLTK v5.3 and the official documentation to learn more about what changes were made and most importantly how they may affect you, especially if you run MLTK models in production.

In today’s digital world, application responsiveness isn’t just an end-user desire but an expectation. Nobody understands the challenges of meeting these demands better than IT, which must remain poised to act when an issue occurs while also finding ways to innovate, improve, and implement continuously.

“Cloud native” – working in distributed systems using microservices and DevOps – has promised a lot, and indeed delivered a lot. Among the biggest benefits, in a cloud-native distributed architecture it’s easier and more cost-effective to scale parts of an application. When one part fails, it is less likely to impact other services and the services can still communicate with each other.

We’re thrilled to announce several new observability features for the Pub/Sub to Splunk Dataflow template to help operators keep a tab on their streaming pipeline performance. Splunk Enterprise and Splunk Cloud customers use the Splunk Dataflow template to reliably export Google Cloud logs for in-depth analytics for security, IT or business use cases.

Over the past year, Grafana Labs has grown from 300 to 700 Grafanistas. Moving forward, we expect to continue to maintain a high rate of change, and to sustain that, we need to ensure there is flexibility in how our teams* are set up. The majority of our Engineering squads have changed in size and structure — and the same goes for the Grafana Observability team, where I work.

Adoption of AWS Lambda functions in cloud-native applications has increased exponentially over the past few years. Serverless functions, such as the AWS Lambda service, provide a high level of abstraction from the underlying infrastructure and orchestration, given these tasks are managed by the cloud provider. Software development teams can then focus on the implementation of business and application logic.

Dear Miss O11y, How is modern observability using tracing, such as Honeycomb, different from the previous distributed tracing software I'm familiar with, like Dapper, at my company? I haven't really been able to wrap my head around Dapper. Does "advanced" observability mean that it's even more complicated than Dapper is? Auntie Alphabet.

We’re excited to announce today Circonus’ Spring ’22 Release, which adds capabilities to further support the observability demands of modern-day enterprises. The Spring Release adds features across all four components of the Circonus platform – Ingestion & Alerting, Visualizations and Reporting, IronDB time series database, and the Circonus Analytics Query Language (CAQL) – with a focus on extending coverage and improving ease-of-use.

A website's performance can be measured using metrics. Metrics provide information on what is working, what is not, and where improvements are needed. Unlike numbers, spreadsheets, or data, it isn't as complicated or as time-consuming to use. For observability in marketing, website metrics that measure user engagement are vital. By analyzing metrics, the marketing department will be able to determine what web pages are not providing the company with value.

Before we take a deep dive into the ways to achieve observability, it is important to understand what observability is and how it is achieved. Frequently, observability is confused with monitoring. Observability provides end-to-end visibility into a system’s internal health by using the data it generates: logs, traces, and metrics. In a multi-cloud environment, observability enables you to detect and resolve anomalies.

Let’s look at IllegalArgumentException, which is one of the most common types of exceptions that Java developers deal with. We’ll see when and why IllegalArgumentException usually occurs, whether it’s a checked or unchecked exception, as well as how to catch and when to throw it. We’ll use a few examples based on common Java library methods to describe some of the ways to handle IllegalArgumentException.

The book is done. The book is FINISHED. There will be no more writing of the book! Holy macaroni. If you think you might be sensing just a SMIDGE of relief, you wouldn’t be wrong. We started writing this book, Observability Engineering: Achieving Production Excellence, three whole years ago, in the summer of 2019. Remember that?

The acceleration in digitalization, also due to the pandemic, has brought an organization’s business and IT teams and strategic goals closer together than ever before. Chief Information Officers (CIOs) have existed since the early 1980s and, until recently, their typical role was primarily focused on managing the technology infrastructure. But in a post-pandemic world, that role is now expanding beyond traditional IT responsibilities.

The Java Collections Framework was a huge leap forward when it was introduced as part of Java 2 (JDK 1.2). Thanks to the included collection classes we finally moved beyond the limits of Vector and Hashtable to more mature and generic solutions. With the introduction of streams and functional concepts in Java 8 the framework took everything to the next level. One of the core principles underlying the framework is coding to the interface.

Clients expect prompt implementation of changes to their software, and this requirement motivates site reliability engineers to incorporate reliability into applications. The healthy practice of observability and monitoring can improve the reliability and security of software systems. Monitoring is the recording and interpreting data from software systems to keep track of their performance.

Having enough time available is a struggle we all experience. Technological innovations enable us to develop and deploy software at lightning speed: Sometimes we can push more to production than our organizations’ IT environments can handle. At the same time, we want to increase customer satisfaction by reducing downtime. But how are you going to keep customer satisfaction rates high if a large majority of incidents are caused by changes?

Tom Granot and myself have had the privilege of Vlad Mihalcea’s online company for a while now. As a result we decided to do a workshop together talking about a lot of the things we learned in the process. This workshop would be pretty informal ad-hoc, just a bunch of guys chatting and showing off what we can do with tooling.

When you migrated critical infrastructure to the cloud, what were your goals and expectations? Odds are, you hoped leaving on-premises infrastructure would produce significant organizational benefits. You probably figured you’d streamline operations and reduce management overhead. You felt you’d have an easier time meeting business goals. Perhaps most important of all, you likely expected your environment would become less complex, and even cost less to operate.

Observability and monitoring is a fundamental part of the contact center environment. When there are thousands of live voice and other multi-channel interactions happening, it is crucial to keep a close eye on the system because any issue in service gives an instant blow to the customer experience. Asterisk is a free and open source framework for building communications applications and is sponsored by Sangoma.

The new release of AppDynamics Monitoring for SAP Solutions continues to evolve in providing broader observability into your SAP environment.

For the last five years, Logz.io has tracked and measured the pulse of DevOps, as well as adoption of key trends and technology, through our DevOps Pulse survey and report. One of the obvious focus areas for us, as a company whose products are based on industry-leading open source, is the increased rise of incredibly useful open-source observability solutions, in general.

I spent over a decade as a consultant working for dozens of companies in many fields and pursuits. The diversity of each code base is tremendous. This article will try to define general rules for modernizing legacy code that would hopefully apply to all. But it comes from the angle of a Java developer. When writing this, my primary focus is on updating an old Java 6 era style J2EE code to the more modern Spring Boot/Jakarta EE code.