Preventing data loss for data in motion is a challenge that Cribl Stream Persistent Queues (PQ) can help prevent when the downstream Destination is unreachable. In this blog post, we’ll talk about how to configure and calculate PQ sizing to avoid disruption while the Destination is unreachable for a few minutes or a few hours. The example follows a real-world architecture, in which we have.

Although microservices and cloud architectures are the new norm for modern applications, cloud cost optimization could run high in observability. High costs are largely due to the number of components involved in cloud architectures. According to Cloud Data Insights in a recent report, around 71% of IT companies say that cloud observability logs are growing at an alarming rate— a driving factor for rising observability costs.

Adaptive thresholding is a term used in computer science and — more specifically — across IT Service Intelligence (ITSI), for analyzing historical data to determine key performance indicators (KPIs) in your IT environment. Among other things, it’s used to govern KPI outliers in an effort to foster more meaningful and trusted performance monitoring alerts.

The process of adding new data to operations and security analytics tools is familiar to admins. New data onboarding can be a tiresome process that takes up too much time and delays getting value from the new data. The process typically begins with the admin engaging the data source owner, getting the wrong data sample, and then having to try again.

DevOps is not just about operating software in production, but also releasing that software to production. Well-functioning continuous integration/continuous delivery (CI/CD) pipelines are critical for the business, and this calls for quality observability to ensure that Lead Time for Changes is kept short and that broken and flaky pipelines are quickly identified and remediated.

Ah, the age-old question of how to manage screen time for kids – it’s like trying to navigate a minefield of Peppa Pig, Paw Patrol, and PJ Masks! I mean, who knew Octonauts and Bubble Guppies would become household names? As a dad of two young kids, managing screen time is a balancing act, especially keeping our 5-year-old happy with access to her shows.

If you’re new to logging, you might be tempted to collect all the data you possibly can. More information means more insights; at least, those NBC “the more you know” public services announcements told you it would help. Unfortunately, you can create new problems if you do too much logging. To streamline your log collection, you can apply some filtering of messages directly from the log source. However, to parse the data, you may need to use a Grok pattern.

In today’s digital landscape, website performance is paramount. To ensure seamless functionality and reliability, businesses rely on Synthetic Monitoring tools. While Pingdom has been a popular choice, it’s essential to explore alternative solutions. In this article, we’ll dive into the top alternatives to Pingdom in 2023, examining their advanced features, functionalities, and integration capabilities.

It’s been about 8 months since we first launched Cribl Search. For our early adopters, it’s been a game changer, and with each monthly release, we continue to innovate — expanding access to new datasets and adding new functionalities. If Crib Search is new to you, here is a quick recap. Cribl Search flips the observability data search paradigm on its head. You no longer have to collect, ingest, and index your data before you can search it.

The latest versions of Elastic Observability’s most popular observability integrations now use the storage cost-efficient time series index mode for metrics by default. Kubernetes, Nginx, System, AWS, Azure, RabbitMQ, Redis, and more popular Elastic Observability integrations are time series data stream (TSDS) enabled integrations.

Elastic Search 8.9 introduces hybrid search with Reciprocal Rank Fusion (RRF) to combine vector, keyword, and semantic techniques for better results. This release also brings performance improvements in vector search and ingestion with response times that are up to 30%+ faster. Users also have more ingestion options with the new SharePoint Online connector, which includes document-level security.

When I was still writing code, our Splunk license only had enough capacity to monitor our Production environment. So we stood up a self-managed Elastic cluster for our lower environments. This quickly became unmanageable as we started logging more and adding additional environments. As I spend more time in the field, I see this pattern repeated over and over.

As an SRE, have you ever had a situation where you were working on an application that was written with non-standard frameworks, or you wanted to get some interesting business data from an application (number of orders processed for example) but you didn’t have access to the source code?

In the realm of Linux system administration, monitoring log files is essential for maintaining a healthy and secure environment. Linux distributions generate a multitude of log files that capture crucial information about system events, errors, and user activities. These log files act as a silent witness, providing valuable insights into the inner workings of a Linux system.

In today’s rapidly evolving digital landscape, organizations heavily rely on their applications and systems to deliver optimal performance. As such, driving down the key metric of Mean Time to Resolution (MTTR) is clearly one of the biggest challenges facing observability practitioners today.

When working with sensitive data, there’s no skimping on security. Keeping data protected and private is paramount at Cribl, which is why we prioritized building a robust framework for Role-Based Access Control (RBAC), and with this latest release, we created an authorization system across the entire Cribl suite. WOOHOO!!

Having a strong full-stack observability has become increasingly crucial in modern IT environments, as organizations strive to gain deep insights into their systems’ behavior, performance and overall health. However, achieving effective observability can be challenging without the right tools and strategies in place. In this article, we will explore the key challenges associated with observability and how Coralogix can help overcome those issues.

With thousands of logs generated every minute from your infrastructure, applications, services, and devices, retaining this copious amount of data for active search and analysis can be cost-prohibitive. Because log volumes continue to grow rapidly as operations scale, it’s common for organizations to implement log management strategies and store only a limited number to minimize costs.

Government and education leaders estimate that data volume at their organizations will increase by 59% over the next three years. Although having more information than you need is (arguably) better than not having it when you need it, the sheer volume of data can make it challenging for teams to pinpoint exactly what data will bring value to their mission goals.

Digital Experience Monitoring (DEM) is a practice that involves monitoring and analyzing the end-to-end digital experience of users interacting with websites, applications, and other digital services. By examining performance, availability, and usability from the end user’s perspective, DEM provides insights into the performance, availability, and usability of these services from the perspective of the end user.

The term index is quite overloaded in the tech world. If you asked most developers what an index is, they might tell you it commonly refers to a data structure in a relational database (RDBMS) that is associated with a table, which improves the speed of data retrieval operations. But what is an Elasticsearch® index?

During our March Cribl User Group livestream, Cribl’s own Eugene Katz covered some of the updates we made to our documentation on Architectural Considerations for deploying Cribl Stream. Topics included our guidelines for determining the ideal number of worker nodes, accounting for throughput variability, and preparing for system failure. The full video has more information on these and other things to consider when determining the right balance between cost and risk for your organization.

How JCB improves team structure, risk management, and application and platform development.

New playbooks can help detect issues automatically and provide support when troubleshooting your GKE environment.

In this blog series, we’ll explore how Corelight and Cribl Stream work together to improve observability in Security Operations Centers (SOCs). In today’s rapidly changing threat landscape, it’s crucial to efficiently monitor and manage data for effective security operations. Corelight provides exceptional network visibility, while Cribl Stream gives you control and the flexibility to optimize data pipelines and gain valuable insights.

Logs are like gold ore. They have valuable nuggets of information, but those nuggets often come in a matrix of less helpful material. Extracting the gold from the ore is crucial because it is vital to unlocking insights and optimizing your system(s). Raw logs can be overwhelming, containing informational messages, debug statements, errors, etc. However, buried within this sea of data lies the key metrics you can use to understand your applications' performance, availability, and health.

Navigating the complex terrain of IT systems, operational issues, and security breaches is no easy job, even for the seasoned CIO. And when tasked with the lofty goals of improving operational resilience, mitigating security risk, and enhancing customer experiences, dealing with the day-to-day operations is all the more challenging. Achieving these goals can often feel overwhelming, with no end to the journey in sight.

In this guide, we will compare two of the leading data visualization tools based upon open-source software that are available for use for metrics, traces and log analysis. To allow new users to know exactly which solution may be best suited to their needs, we wanted to explore in more depth a comparison between OpenSearch Dashboards and Kibana across various aspects in our latest guide covering the differences between leading open-source software.

Logz.io is excited to announce Service Overview, a fast and easy way to unify telemetry data and insights across your infrastructure and applications into a single interface. Our Beta users have reported simplified observability, faster time-to-insights, and observability consolidation.

In a rapidly evolving realm of IT, organizations are constantly seeking peak performance and dependability, leading them to rely on a reliable observability platform to obtain valuable system insights. Logs vs metrics play a vital role, as any full-stack observability guide would tell you, serving as essential elements for efficient system monitoring and troubleshooting. But what are logs and metrics, exactly?

The common failure scenarios that occur in the cybersecurity world are typically assumed to be costs of doing business, but they’re actually more predictable and avoidable than you might imagine. Even if you’ve been lucky enough to avoid failed data sources or backups, a SIEM getting knocked offline, and other cybersecurity attack situations until now — in today’s day and age, they’re still inevitable.

Hey there, Cribl fans! We hope you’re ready to move into the second half of summer with a splash because we have some exciting news to share. Our latest product launch is all about enabling teams and multiple users to work together seamlessly while focusing on security, access control, and providing valuable data insights on demand. Who says you can’t have it all? Let’s dive right into the details!

Elastic APM supports OpenTelemetry on multiple levels. One easy-to understand scenario, which we previously blogged about, is the direct OpenTelemetry Protocol (OTLP) support in APM Server. This means that you can connect any OpenTelemetry agent to an Elastic APM Server and the APM Server will happily take that data, ingest it into Elasticsearch®, and you can view that OpenTelemetry data in the APM app in Kibana®.

Red Hat is a Linux distribution known for its stability, security, and enterprise-grade features. Whether you’re running Red Hat on bare metal servers or virtual machines, monitoring the performance of your infrastructure is essential. In this article, we’ll explore the top performance monitoring tools for Red Hat servers. We’ll compare their pros, cons, and pricing to help you make an informed decision.

Elasticsearch® recently released time series data streams for metrics. This not only provides better metrics support in Elastic Observability, but it also helps reduce storage costs. We discussed this in a previous blog. In this blog, we dive into how to enable and use time series data streams by reviewing what a time series metrics document is and the mapping used for enabling time series. In particular, we will showcase this by using Elastic Observability’s Nginx integration.

Many of us remember the public service announcements asking parents if they knew where their kids were at night. They were ominous and a little alarming. Asking yourself the same question about your data can be equally as scary, but Cribl Edge can help.

We’re thrilled to announce new feature updates for Logz.io’s Kubernetes 360 to provide deeper visibility and additional troubleshooting capabilities for your Kubernetes environment.

In the face of growing security threats and incidents, businesses must prioritize their ability to detect, investigate, and respond effectively. Timely incident response is crucial for maintaining the security and integrity of systems and data. Among the essential tools in the incident response arsenal, log monitoring stands out as a critical component. By closely analyzing logs, organizations gain valuable insights into system events, user activities, and network traffic.

The Elastic APM Java Agent automatically tracks many metrics, including those that are generated through Micrometer or the OpenTelemetry Metrics API. So if your application (or the libraries it includes) already exposes metrics from one of those APIs, installing the Elastic APM Java Agent is the only step required to capture them. You'll be able to visualize and configure thresholds, alerts, and anomaly detection — and anything else you want to use them for!

As someone who admittedly gets bored easily, one of my favorite things about working for a company like Cribl is the huge amount of technologies in our ecosystem I get exposure to. Over time, I also get to observe trends in the market – it’s always so cool to see big upswings in adoption for various platforms and tech. One such trend I’ve observed over the last year is a noticeable uptake and presence in the market of Google Chronicle.

Python is a highly skilled language with a large developer community, which is essential in data science, machine learning, embedded applications, and back-end web and cloud applications. And logging is critical to understanding software behavior in Python. Once logs are in place, log monitoring can be utilized to make sense of what is happening in the software. Python includes several logging libraries that create and direct logs to their assigned targets.

Event Hubs is Microsoft’s cloud-native real-time event streaming service. For Event Hubs to work, data must be pushed to or pulled from it. That is where Cribl Stream comes in. Event Hubs is a source and destination inside Cribl Stream and the control for how you route, shape, and transform your data from Event Hubs. But, one does not simply Stream into (or from) Event Hubs. There is a lot that goes into architecting an Event Hubs Source.

Consistent performance and continuous improvement: these are the fundamentals we should aspire to in the world of cloud software delivery. We focus on ensuring our systems become more consumable, enjoyable and innovative. We seek to make customers’ lives easier and more productive through incremental achievements, and doing a better job, every day.

Container monitoring refers to the process of monitoring and managing containers deployed within a containerization platform, such as Docker or Kubernetes. As containerization has become increasingly popular in software development and deployment, monitoring and managing containerized environments has become increasingly important.

A comprehensive guide to support faster drug innovation and discovery in the pharmaceutical industry with generative AI/LLMs, custom models, and the Elasticsearch Relevance Engine (ESRE) Faster drug discovery leading to promising drug candidates is the main objective of the pharmaceutical industry. To support that goal, the industry has to find better ways to utilize both public and proprietary data — at speed and in a safe way.

Psst, hey pal, would you like to buy a time machine? I am not talking about some H.G. Wells monstrosity where you somehow end up being chased by dinosaurs or become your own grandparent. But a time machine for your observability data. License costs and tool performance often keep organizations from ingesting all their data or require them to limit data retention time. Security incidents are often discovered long after these retention times are exhausted or require data that was never ingested.

One of the most important events you should be monitoring on your network is failed and successful logon events. What comes to most people’s minds when they think of authentication auditing is OS level login events, but you should be logging all authentication events regardless of application or platform. Not only should we monitor these events across our network, but we should also normalize this data so that we can correlate events between these platforms.

In the highly competitive IT industry, staying ahead of the curve is crucial for success. As IT companies strive to meet the evolving needs of their customers, they are discovering that providing embedded services and comprehensive training can significantly enhance their sales efforts. The importance of having services is discussed in this Harvard Business Review article.

Whenever an event occurs on your Windows machine, the operating system records an event log that includes details about the nature of the event (e.g., critical runtime error) or security identifiers (for audit events). Windows event logs not only record system and application activity but also user actions and background processes, making them an invaluable tool for monitoring the security and health of your systems.

Observability is essential for maintaining the performance and reliability of modern software systems. However, the cost associated with attaining and extending observability can quickly escalate in ways that may not even seem apparent at first. We hear from many organizations struggling to tamp down the costs of observability at a time when every dollar spent on technology is scrutinized.

Can you believe we’re already halfway through 2023? Time flies when you’re busy innovating and having fun (yet somehow also seems so slow when you are waiting for your next vacation!!). At Cribl, we’ve been hard at work releasing wave after wave of incredible new features and capabilities across our entire product suite.

Today I want to talk about metric queries. More specifically, I want to talk about an important concept that is going to make your queries run faster, give you more accurate results, and make your Grafana Loki operators (like me) much happier. A metric query in Loki looks like this: And the part I want to talk about is that at the end. Now, if you’re like me and have a short attention span and are already bored — I understand.

Cloud monitoring tools are utilized to gather an extensive range of metrics and logs from cloud resources and services. Some commonly monitored metrics include CPU utilization, memory usage, network traffic, disk I/O, latency, and response time. By monitoring these metrics, among others, it becomes possible to gain insights into resource utilization, identify performance bottlenecks, and ensure that the infrastructure operates according to expectations.

For a game to provide the best user experience, certain elements come into play. These factors can be hardware components in the user’s computer, like the CPU and GPU, operating system settings, or specific game settings. In fact, if there’s misalignment between these components and a game’s intensity, performance issues can crop up. The most common performance issues in gaming include frame rate drops, input lag, stuttering, rendering issues and network latency.

The popularity of open-source log management tools has been on a steady rise in recent years. As businesses become increasingly reliant on software applications and cloud-based services, logging has become an essential part of operations. Log management is a crucial process for organizations to collect, store, and analyze log data. Businesses can troubleshoot problems, identify security threats, and optimize system performance by effectively managing log data.

In this tutorial, we will guide you through the process of migrating from Elasticsearch to OpenSearch. OpenSearch is aan open-source search and analytics suite that is compatible with Elasticsearch. There are several reasons why people choose to migrate, such as taking advantage of new features or differences in governance. In the following sections, we will discuss version compatibility considerations, and guide you through the migration process.

In the ever-evolving world of search engines, Elasticsearch, OpenSearch, and Solr have long held the spotlight. However, there are several smaller search platforms that pack a punch and offer compelling alternatives. In this article, we will explore 11 small search platforms, delving into their major features, pros, and cons.

As a leading full-stack observability platform, Coralogix enables you to gather, monitor and analyze your infrastructure and application telemetry. And Coralogix now offers synthetic monitoring for proactive end-to-end testing across development with Checkly.

Generally, data monitoring can be referred to as a continuous process of observing and tracking data in order to ensure its integrity, quality, and conformance with specific standards or requirements. Data monitoring often involves systematic data collection, analysis, and reporting to identify patterns, trends, anomalies, and potential issues.