Log management tools provide visibility into the performance and behavior of systems, applications, networks, and infrastructure components. By collecting and analyzing logs, you can monitor for anomalies, track trends, and identify potential issues before they escalate. Choosing the right log management solution requires careful consideration of several factors to ensure that it meets your specific needs and goals. Here are the most popular open source log management tools to help you choose.

There’s a sentence that strikes fear into the heart of every frontend developer I've ever met: Users are reporting issues, and we don't know how to replicate them. What do you do when that happens? Do you cry? Do you mark the issue as wontfix and move on? Personally, I took the road less traveled: gave up frontend engineering and moved into product management (this is not actually accurate but it's a good joke and it feels truthy).

Cisco Full-Stack Observability is a strategic investment that outshines Dynatrace by incorporating AI-driven insights, full-stack visibility, and a future-proof design that adapts to your evolving business needs. Application experience is the heart of your digital business, so choosing the right observability platform is not just a technical decision — it’s strategic.

StackState had a blast at this year's KubeCon + CloudNativeCon gathering in Paris! The discussions were in-depth, covering a wide array of topics and lasting much longer than in the past. This year, attendees seemed to have a considerably deeper understanding of the cloud-native ecosystem, probably attributed to its rapid growth. We also noticed a pretty dramatic evolutionary shift in the vendors at the expo hall, who were showcasing some truly progressive specialized solutions.

Kubernetes has changed the way many organizations approach the deployment of their applications. But despite its benefits, the additional layers of abstraction and reams of data can cause complexity around Kubernetes monitoring. We’ve seen so much of these challenges borne out in the results of the 2024 Observability Pulse survey. In the survey report, 36% of respondents say Kubernetes poses a challenge, and just 10% of organizations say they have full observability into their environments.

The concept of observability has become a cornerstone for ensuring system reliability and efficiency in modern software engineering and operations. Observability, beyond its traditional scope of logging, monitoring, and tracing, can be intricately defined through the lens of incident response efficiency—specifically by examining the time it takes for teams to grasp the full context and background of a technical incident.

The Uptrace team is pleased to present the latest v1.7 release, which introduces dark mode, revamped navigation, dashboards list, system tracing metrics, and much more.

Observability has emerged as a distinct approach within the broader scope of IT management, enabling organizations to gain valuable insights into their complex IT ecosystems. By collecting and analyzing data from various sources, observability provides a holistic understanding of system behavior and performance, streamlining troubleshooting and optimization efforts.

Microsoft Azure provides an array of managed services to support many aspects of cloud computing, including application development, workload migration, and data management. To help you monitor the health and performance of these services, Datadog offers integrations with more than 40 Azure services, including Azure Kubernetes Service (AKS), Cosmos DB, and Azure App Services. Each integration provides robust data visualizations, meaningful alerts, and one-click Datadog Agent deployment.

The expenses associated with collecting, storing, indexing, and analyzing data have become a considerable challenge for organizations. This data is growing as fast as 35% a year, multiplying the problems. This surge in data comes with a corresponding rise in infrastructure costs. These costs often force organizations to make decisions about what data they can afford to analyze, which tools they must use, and how and where to store data for long-term retention.

Observability tools help engineering teams understand the health and behavior of software. But the term “health” in the context of this type of tooling is fairly narrow in scope—pertaining to real-time performance, reliability, and availability. While these are three important metrics to monitor, they’re lagging indicators of bigger issues happening upstream.

If you are an MSP, AIOps can be a game changer for your business. By leveraging AI-driven automation, analytics, and insights across your managed IT services portfolio, you can drive operational excellence, improve service quality, and deliver greater value to your clients. But there are many AIOps and observability tools in the market. Here are 13 reasons why many MSPs select Virtana as their AIOps and observability partner of choice.

Manage and correlate signals and alerts in Elastic Observability As organizations embrace increasingly complex and interconnected IT systems, the sheer volume of alerts generated by diverse monitoring tools has given rise to a critical challenge — how do we efficiently sift through the noise to identify and respond to the most crucial issues? Event management and correlation are two indispensable pillars in the realm of IT service management.

The more data you have, the harder it becomes to read through it, let alone identify trends or crucial patterns. Couple that with a shortage of time, and the ability not only to visualize but also to communicate with your data becomes paramount.

IT teams are the invisible engines powering every modern organization. Yet they battle constantly to ensure the availability and reliability of applications and services across fragmented, hybrid-cloud infrastructures. In particular: Fragmented tools, siloed workflows, and inconsistent manual processes create an IT nightmare. Despite investing millions in observability and ITSM platforms, teams face alert fatigue, reactive incident response, and persistent outages.

The ability to peer deeply into the inner workings of software and systems isn’t just advantageous – it’s essential. Observability, a term that’s gaining traction among tech professionals, stands at the forefront of this shift, empowering software engineers and DevOps teams with the clarity and insight needed to steer complex systems toward optimal performance.

We know monitoring your AWS environment can be difficult, which is why we’re thrilled to tell you about a new application we’ve built to make the entire process easier, more efficient, and more intuitive. We’ve offered AWS monitoring capabilities for some time, but with the AWS Observability application in Grafana Cloud, we’ve distilled our collective efforts into a more integrated and potent solution.

As a new company poised to transform the financial services industry with its modern money movement platform, Moov wanted an equally modern observability platform as part of the company’s operational tech stack. With Moov's platform hosted in Google Cloud, it uses a diverse range of technologies to allow clients to accept, store, send, and spend money. The integration of numerous software providers further amplifies the complexity of each transaction.

As organizations increasingly depend on distributed system architectures to provide modern applications and microservices, their legacy monitoring tools struggle to keep pace. These outdated systems are often based on predictable failures, but when an unforeseen performance issue occurs, it can lead to outages and unplanned downtime that impacts your customers and your business.

In this blog post, we'll dive into the critical role of application observability in maintaining optimal performance and uptime. We'll explore how it works, why it's essential, and how it transforms challenges into opportunities for growth and improvement. So, if you're looking to elevate your application's performance and reliability to new heights, you're in the right place.

Imagine you are driving a car with no dashboard. You can't see the speed, fuel level, or engine temperature. You are flying blind, hoping everything is okay until something goes wrong. This is what it's like to manage complex IT systems without observability. Observability is the key to understanding the internal state of a system. It is crucial for detecting and resolving issues efficiently, reducing downtime and costs.

Imagine you're leading a team of engineers responsible for monitoring and optimizing the performance of a cloud-based application used by millions of users worldwide. As the application continues to scale, you recognize the pressing need for a robust observability solution to learn about its distributed architecture. In this scenario, you're faced with an essential decision: choosing between OpenTelemetry and Datadog for distributed tracing and observability.

There’s been a lot of recent interest in eBPF (extended Berkeley Packet Filter) and its application for container security solutions. Let’s examine eBPF’s features and benefits and how NeuVector utilizes them to enhance its full-lifecycle container security solution.

Cisco’s one-of-a-kind conference, Cisco Live EMEA 2024 in Amsterdam, marked a pivotal milestone in illuminating the path forward with a spotlight on AI, operational simplicity, and security. Bringing key network telemetry and correlating it with the business outcomes has become quite essential for Modern Enterprises and CloudFabrix addressed this by launching three new modules for the Cisco Observability Platform.

According to PYPL (PopularitY of Programming Language), Python has been the most popular programming language worldwide from 2018 to the present. Remarkably, Python’s popularity has grown by 2.5% over the last five years. In contrast, Java, the previously most popular language, has seen a 4.8% decrease in its popularity. While Java is typically faster than Python, Python is easier to read with its simpler syntax.

If you’ve been keeping up on what’s buzzing in the IT operations and software development space in the past few years, then you know that the concepts of AIOps and observability have been getting a lot of attention. And while they are related, they each address a different aspect of managing and monitoring IT systems.

For years, we’ve been installing what vendors have referred to as “agents” that reach into our applications and pull out useful telemetry information from them. From monitoring agents, to full-blown APM tools, this has been the standard for many decades. With OpenTelemetry though, the term “agent” isn’t used as much, and in most scenarios means something slightly different.

Modern hybrid IT estates generate huge volumes of data at velocity, a testament to today’s digital reality. But for IT Operations Management (ITOM) teams charged with keeping tabs on system health, this data proliferation can be a nightmare scenario. Tool sprawl, alert storms, manual analysis, and disconnected insights make maintaining a current state, let alone supporting better business outcomes, a perpetual challenge.

Observing Edge & WAF solutions is challenging. There are a host of unique problems to overcome, including security complexities and traffic intent identification. Let’s explore the complexities of observing edge data and how Coralogix’s revolutionary features take an entirely new approach to edge observability.

Organizations like yours are increasingly reliant on complex IT infrastructures to support their operations. Pervasive use of Kubernetes and microservices architectures continues to up the ante. Amidst this complexity, achieving comprehensive visibility into systems and applications has become both imperative for ensuring performance, reliability, and security, while also becoming ever-more challenging to achieve.

We're excited to unveil a new collaboration with Focused Labs, a leap forward in our shared commitment to advancing modern observability practices and enhancing the robustness of legacy systems. This partnership is not just about scaling our service offerings but also about integrating Focused Labs' deep engineering expertise with our observability platform to deliver unparalleled customer experiences.

Regardless of the industry they operate in or the number of people they employ, businesses with mature observability practices can respond to incidents faster — and save time and money in the process, according to the second annual Grafana Labs Observability Survey. Organizations are making observability a critical part of their software development lifecycles as they grapple with the complexity of modern applications.

SolarWinds® Observability now brings more intelligence to issue identification to help you troubleshoot smarter and faster. When an entity alert is triggered, Log Patterns automates an AIOps / ML-based analysis of events surrounding the triggering event. Using Log Patterns, you can skip the hours spent manually scrolling through event messages looking for unusual or significant patterns.

Now, many teams are incorporating microservices architecture, with this trend only continuing. This allows them to employ their applications across distributed environments. Whilst this is advantageous as it makes it much simpler to build, scale, and deliver it can also become much more challenging to monitor and troubleshoot the components that make up the environment.

In the dynamic landscape of financial services, data is not just currency; it's the key to innovation and operational excellence. Data is constantly streamlining from devices, logins, transfers, transactions, and much more, and it’s bound to increase with an ongoing reliance on digital channels. This creates a massive opportunity and responsibility for financial institutions, as their customers (and regulators) demand more from banking providers.

Naming things, and specifically consistently naming things, is still one of the most useful pieces of work you can do in telemetry. It’s often overlooked as something that will just happen naturally and won’t cause too much of an issue—but it doesn’t happen naturally, it does cause issues, and you end up having to fix the data in pipelines or your backend tool.

See the results of our 2024 survey of over 500 observability decision-makers to find out where the industry is headed As technology evolution continues at its rapid pace, so does observability. Observability is becoming critical to driving positive business outcomes, and we wanted to understand how users are evaluating trends and their impact over the coming years.

Phorest wanted a tool to help foster a culture of observability among the engineers at an affordable and predictable price. With their application stack hosted on AWS, Phorest delivers a premier software solution that empowers their salon and spa business customers to thrive. Ensuring every engineer has access to an observability tool is integral to the company's success model, enabling them to deliver great code for their designated software services.

In this post, I describe how to send OpenTelemetry (OTel) data from an AWS Lambda instance to Honeycomb. I will be showing these steps using a Lambda written in Python and created and deployed using AWS Serverless Application Model (AWS SAM).

Distributed tracing tools are essential in modern software development and operations for monitoring, troubleshooting, and optimizing complex distributed systems. The best tracing tools can help you eliminate performance bottlenecks and recover from incidents faster. Use this guide to pick the right one for you.