The dynamic nature of the IT landscape poses complex challenges for organizations, necessitating the involvement of observability engineers. These skilled professionals have become indispensable in addressing critical pain points and optimizing system performance. In this blog post, we delve into the challenges observability engineers face and showcase how Mezmo's comprehensive telemetry solution empowers them to overcome these hurdles and achieve optimal results. ‍

Pressure is mounting for organizations to deliver exceptional customer and employee experiences, rapid event resolution, and better business outcomes. Observability will be a key strategy play to achieve end-to-end visibility of complex tech estates, says Pablo Stern, senior vice president of technology workflows at ServiceNow. In an interview at Knowledge 2023, Stern talked about how an observability platform can encompass both DevOps workflows and business processes across the enterprise.

One of the most captivating discussions I had at KubeCon Europe 2023 in Amsterdam was about standardization of a query language for observability. This query language standard aims to provide a unified way of querying observability data across logs, metrics, traces, and other relevant signals. The conversation shed light on the pressing need for a standardized approach to overcome the challenges posed by the plethora of query languages currently in use.

This week Lightrun attended the annual FinOps X event. The event was sold out and packed with great speakers, practitioners, and amazing atmosphere. Compared to last year which had over 300 attendees, this year the event brought over 1200! Above is a screenshot taken from the venue entrance reminding the audience with the core principles of FinOps.

During the second quarter of this year, Lightrun persisted producing a wealth of developer productivity solutions and enhancements, aiming for greater troubleshooting of distributed workload applications, reduction of MTTR for complex issues, and cost optimization within cloud-computing. Read more below the main new features as well as the key product enhancements that were released in Q2 of 2023!

Kentik customers can now map traffic and performance of Microsoft Azure infrastructure with visibility into Azure Firewalls, Express Routes, Load Balancers, VWANs, and more in Kentik Cloud.

In my previous blog post, I discussed how transitioning from legacy monolithic applications to microservices based applications running on Kubernetes brings a range of benefits, but that it also increases the application’s attack surface. I zoomed in on creating security policies to harden the distributed microservice application, but another key challenge this transition brings is observing and monitoring the workload communication and known and unknown security gaps.

Asaf and I founded Logz.io in 2015 to provide developers with the ultimate open source log management experience. With our product, logging with the ELK Stack was simple, efficient, and automated for the first time – so customers could save engineering costs and accelerate MTTR.

Insightful proof-of-concepts with a tool can be difficult to undertake due to the demands on valuable resources: time, energy, and people. With a task as grand as observability, how could one truly test if Honeycomb and OpenTelemetry are right for their organization and meet their requirements? For this thought experiment, here’s a comprehensive description of the ideal product evaluation over the course of four weeks, given unlimited resources.

Managing over 1000 services and applications is daunting for any organization’s IT and Tech operations team. With a diverse mix of on-premises legacy systems and modern cloud stacks, the sheer volume of activity can overwhelm even the most skilled ITOps teams. The task is made more difficult by the fact that observability is fragmented. On average, organizations depend on 21 systems that produce metrics, logs, traces, and alerts for various services.

Centralized Observability may not be a buzzword but its practicality and importance can’t be denied. Let’s see why is that. As DevOps and IT teams recognize the importance of Observability, it becomes a critical component to monitor the stack and ensure data reliability. That being said, enterprises are rapidly embracing modern data stacks to harness the power of data. Therefore, a host of platforms require data observability as a tool for reliable and trustworthy data management.

In my previous articles, I discussed how to design considerations for observability solutions and how observability can augment your security implementation. In this article, I will discuss how an observability solution can provide valuable insights into your business operations through the collected data from various systems, applications, and services.

People seem to struggle with the idea that there are no repeat incidents. It is very easy and natural to see two distinct outages, with nearly identical failure modes, impacting the same components, and with no significant action items as repeat incidents. However, when we look at the responses and their variations, we can find key distinctions that shows the incidents as related, but not identical.

OpenTelemetry and Beelines were designed with assumptions about the types of traffic that most users would trace.

Today we’re happy to announce our new open source, scalable logging solution, VictoriaLogs, which helps users and enterprises expand their current monitoring of applications into a more strategic ‘state of all systems’ enterprise-wide observability. Many existing logging solutions on the market today offer IT professionals a limited window into live operations of databases and clusters.

AWS Fargate is a serverless pay-as-you-go engine used for Amazon Elastic Container Service (ECS) to run Docker containers without having to manage servers or clusters. The goal of Fargate is to containerize your application and specify the OS, CPU and memory, networking, and IAM policies needed for launch. Additionally, AWS Fargate can be used with Elastic Kubernetes Service (EKS) in a similar manner.

At Honeycomb, we are all about observability. In the past, we have proposed observability-driven development as a way to maximize your observability and supercharge your development process. But I have a problem with the terminology, and it is: I don’t want observability to drive your development.

In today’s data-driven world, the need for comprehensive observability has never been greater. Organizations rely on observability to gain insights into their systems’ and applications’ performance, availability, and behavior. However, the traditional approach to observability, which involves ingesting, processing, and storing massive amounts of data, is becoming increasingly challenging and expensive.

Fintech companies operate in a complex technological and regulatory environment. They rely heavily on cloud-native technologies and microservices architectures to handle financial transactions and data, often at a massive scale. To maximize application reliability, fintech companies need full visibility into their software systems and applications. An agile monitoring solution like observability is crucial to improving performance and user experience.

Cribl has a unique position right in the middle of the observability market, giving us a distinct view of all things security, APM, and log analysis. Observability as a concept has exploded into specialized areas over the past two years, and making sense of the players and market forces, particularly in a difficult macro environment, can be tricky. Let’s break it down.

Code instrumentation is an essential practice in modern software development. Not only does it aid in debugging, it ultimately impacts the MTTR (Mean Time to Resolve) for software running in production. With changing software architectures and deployment patterns over the years, approaches to code instrumentation have also undergone a significant shift.

Quickly: if you’re interested in observability for LLMs, we’d love to talk to you! And now for our regularly scheduled content: In early May, we released the first version of our new natural language querying interface, Query Assistant. We also talked a lot about the hard stuff we encountered when building and releasing this feature to all Honeycomb customers. But what we didn’t talk about was how we know how our use of an LLM is doing in production!

On June 28th I will be hosting a webinar, ‘The Fundamentals of Searching Observability Data’. So why should you attend? Because things have, and will continue to change in the way we manage the IT data collected across the enterprise. A recent study shows that enterprises create over 64 zettabytes (ZB) of data, and that number is growing at a 27 percent compound annual growth rate (CAGR). The scary part?

In Elasticsearch 8.8, we’re introducing the reroute processor in technical preview that makes it possible to send documents, such as logs, to different data streams, according to flexible routing rules. When using Elastic Observability, this gives you more granular control over your data with regard to retention, permissions, and processing with all the potential benefits of the data stream naming scheme. While optimized for data streams, the reroute processor also works with classic indices.

Application Programming Interfaces (APIs) are a crucial building block in modern software development, allowing applications to communicate with each other and share data consistently. APIs are used to exchange data inside and between organizations, and the widespread adoption of microservices and asynchronous patterns boosted API adoption inside the application itself.

The benefits of going cloud-native are far reaching: faster scaling, increased flexibility, and reduced infrastructure costs. According to Gartner®, “by 2027, more than 90% of global organizations will be running containerized applications in production, which is a significant increase from fewer than 40% in 2021.” Yet, while the adoption of containers and Kubernetes is growing, it comes with increased operational complexity, especially around monitoring and visibility.

Today’s IT systems are ever more fragmented. It is commonplace to see polyglot systems, written in multiple programming languages, and using a plethora of tools and cloud services as infrastructure building blocks, whether data stores, web proxy or other functions. In this dynamic cloud-native realm, open standards and open specifications have become integral drivers of compatibility, collaboration, and convergence – the Three C’s of Open Standards, if you will.

We're thrilled to announce the launch of Rollbar's latest initiative to provide greater transparency and control over your occurrences. Our team has worked hard to address customers' feedback and concerns based on your occurrences and overages. We are excited to introduce a new level of observability to our platform.

IT, DevOps, and security teams are figuring out the best ways to manage their complex, ever-growing, ever-changing environments. And one contributing factor to all the complexity is the rise of using multiple cloud services. One cloud service to manage is difficult enough, but adding more to the mix — each with its own interface and set of tools — makes everyone’s job significantly more difficult.

We saw a shift this year in how the technology sector honed in on sustainability from a cost perspective. In particular, looking at where they’re spending that revenue in the infrastructure and tooling space. Observability tooling comes under a lot of scrutiny as it’s perceived as a large cost center—and one that could be cut without affecting revenue. After all, if the business hasn’t had a problem in the last few months, we mustn’t need monitoring—right?

While Kubernetes comes with a number of benefits, it’s yet another piece of infrastructure that needs to be managed. Here, I’ll talk about three interesting ways that Honeycomb uses Honeycomb to get insight into our Kubernetes clusters. It’s worth calling out that we at Honeycomb use Amazon EKS to manage the control plane of our cluster, so this document will focus on monitoring Kubernetes as a consumer of a managed service.

Serverless, as you may already know, is a cloud computing model where the cloud provider dynamically manages and allocates resources to execute code without the need for server provisioning or infrastructure management on the developer. This article overviews serverless observability, monitoring, and debugging, based on distributed tracing and OpenTelemetry (OTel).

We are excited to share that the AIOps and Observability solution from Broadcom has earned a leader position for platform play and maturity in the GigaOm Radar Report for Cloud Observability, 2023. This report reviewed solutions from 20 vendors on 13 criteria, including across such areas as innovation, understanding of emerging trends, solution capabilities and features, and deployment models.

Kubernetes is the gold standard for container orchestration at scale. While massive global companies like Google, Spotify, and Pinterest rely on Kubernetes to run their software in production, so do many small but mighty developer teams. (Full disclosure: Honeycomb joined the Kubernetes brigade last year, when we migrated some of our services.)

Today, I’ll cover the benefits of monitoring and observability in Nutanix AHV environments and Hyper Converged Infrastructures (HCI) and how observability can help IT teams run cost-efficient, performant Nutanix deployments. Modern enterprises need infrastructures designed for resilience, cost-effectiveness, and application performance. Organizations are adopting hybrid multi-cloud strategies and looking to simplify and optimize on-premises and data center operations.

Limited visibility into network performance across multi-clouds frustrates even the best teams. That’s why we’re thrilled to announce enhanced AWS and GCP support for Kentik Cloud, enabling network, cloud, and infrastructure teams to rapidly troubleshoot and understand multi-cloud traffic.

Are you getting value for every dollar spent on IT monitoring tools? Amidst the prevailing global economic turbulence, budgets are shrinking, and every dollar spent counts. However, Gartner forecasts a 5.1% growth in worldwide IT spending for 2023. Enterprises implement digital technologies to cope with layoffs and keep their systems up. The million-dollar question is: Is the monitoring output worth the cost of the monitoring solution?

Running a Kubernetes cluster isn’t easy. With all the benefits come complexities and unknowns. In order to truly understand your Kubernetes cluster and all the resources running inside, you need access to the treasure trove of telemetry that Kubernetes provides. With the right tools, you can get access to all the events, logs, and metrics of all the nodes, pods, containers, etc. running in your cluster. So which tool should you choose?

In Kubernetes, the Domain Name System (DNS) plays a crucial role in enabling service discovery for pods to locate and communicate with other services within the cluster. This function is essential for managing the dynamic nature of Kubernetes environments and ensuring that applications can operate seamlessly. For organizations migrating their workloads to Kubernetes, it’s also important to establish connectivity with services outside the cluster.

Integrating network intelligence and application observability, our latest Customer Digital Experience Monitoring enhancement enables end-to-end visibility and eliminates silos.

Coming soon – new cloud native and data security capabilities to keep business-critical applications protected with the power of Cisco Security integrations.

The concept of observability centers around collecting data from all parts of the system to provide a unified view of the software at large. Fault tolerance, no single point of failure and redundancy are prominent design principles in modern software systems. But that doesn’t mean errors, degradation, bugs or even the occasional catastrophe don’t happen.

Martin and Jess recently conversed with Todd Gardner of RequestMetrics as part of the O11ycast podcast. We don’t normally write blogs based on these conversations, but there were impactful comments in that episode that bear repeating. You can listen to the full conversation if you wish. Let’s get into it!

Monitoring APIs through enhanced observability has gained traction with the popularity of microservices. Since microservice applications are built as independent and scalable modules, the number of microservices can grow dramatically as the application grows, increasing the complexity drastically. Since APIs work as the connective tissue between microservices, the number of APIs also grows in parallel.

Administrators and IT management are increasingly leveraging simple quantifiable KPI indicators such as “Performance Ratings” to gain rapid overviews and track key outcomes. Modern IT architectures are designed and built to scale and be resilient. Systems are now usually built to handle failover and auto-scale up and down to handle varying demand and workloads with very different properties and needs.

In a simple deployment, an application will emit spans, metrics, and logs which will be sent to api.honeycomb.io and show up in charts. This works for small projects and organizations that do not control outbound access from their servers. If your organization has more components, network rules, or requires tail-based sampling, you’ll need to create a telemetry pipeline.