If you’re unfamiliar with observability, you might think an “observability engineer” is just a fancy way to say data admin — but while observability engineers often work with data admins, they work toward different goals. Data admins monitor information to identify and fix known security issues. Observability engineers work to provide a complete picture of all the data a company aggregates and what it means for a business.
I like to leverage our technologies to ensure our products have a pleasant user experience. Elastic Synthetics enables you to configure it in an out-of-the-box experience directly through your Elastic Cloud deployment without the need to install anything! It also works across the globe with multiple locations you can choose from. Ever wondered how fast your web service is when accessed from Japan, Germany, or the eastern U.S.? Now you can do this by simply clicking on a checkbox.
Cloud Logging launched Log Analytics powered by BigQuery. The top 10 reasons to get started with Log Analytics for no additional cost
When I speak with customers, especially chief information security officers (CISOs), one of their most consistent requests is that they want interoperability. They want the software they buy to work with the software they have and plan to buy in the future. Nearly every organization, certainly every enterprise company, has an installed base of hardware and software representing a significant investment in time and money.
Hopefully by now you’re taken your first sip of Elastic RUM, or real user monitoring, and see the power of searching through traces and the User Experience metrics to gain insights into how users actually use and experience your application. One issue you may have experienced is the challenge of finding the source of errors for minified JavaScript files.
Virtually every business utilizes some form of data collection, no matter how big or small. While large-scale enterprises have more established methods for collecting, storing and analyzing data, smaller companies and start-ups are also beginning to understand the value of data collection and analysis in order to: This is especially true in the age of Big Data and democratized data — where we have more data-driven insights available to us than ever.
When you first hear “Robotic Process Automation” (RPA) you might immediately think of a manufacturing line with a series of physical robots each doing their part to build something. RPA is SO much more than that! The “bot” in this sense is an AI powered piece of software that can interface with any system you run today just as a human would.
Automatic UI Updates (AUIU) is a new cloud service that allows admins to get the most up-to-date UI experience between Splunk Cloud upgrades. Cloud admins gain early access to newly enhanced self-service tools through the AUIU opt-in service. Specified AUIU enhanced pages and tooling can now be delivered to customers up to three months faster. AUIU is a delivery service that allows for new UI pages and UI improvements to be integrated into Splunk Cloud deployments for specific enhanced admin pages.
The best part of my job is talking to you, our prospects, and customers, about your logging and data practices. I love listening to what you are doing and hope to accomplish, so I can get a sense of the end state. My goal is to brainstorm solutions that provide overall value across the enterprise, and not just aim for a narrow tactical win with limited impact. In late September, I hung out at a local DevOps conference in Brooklyn with the NYC Cribl sales team.
This is a beta for the upcoming release of Graylogv5.0. Please read on for detailed descriptions of everything that is included.
How enterprises store and split up observability and security data is a great analogy to how lint, spare change, and partially-eaten bags of popcorn end up under couch cushions. Or when you tell your kids to clean up the house when company is coming over and they stash their toys and your tools in various nooks and crannies.
Organizations of all sizes rely on their observability data to drive critical business decisions. Production Engineers across Development, ITOps, and Security use it to understand their systems better, respond to issues faster, and ultimately provide more performant and secure user experiences. But while the value of observability data is well understood, teams struggle to derive value from it.
HAProxy is generally the frontend layer of your application, which means it plays a critical role since all traffic first lands on this layer. Because of this, you need to make sure everything is working at this layer all the time, as any issue can directly impact your business. Therefore, having visibility on this layer is crucial. Visibility can come from two aspects: the metrics HAProxy emits and the logs it generates while handling requests.
Understanding if your applications are not just available but also functioning as expected is critical for any organization. Third-party dependencies and different end-user device types means that infrastructure monitoring and application observability alone are not enough to spot and minimize the impact of application anomalies.
Microservices architecture is the new norm for building products these days. An application made up of hundreds of independent services enables teams to work independently and accelerate development. However, such highly distributed applications are also harder to monitor. When hundreds of services are traversed to satisfy a single request, it becomes difficult to investigate system issues.
Ask any cloud software team using Kubernetes (and most do); this powerful container orchestration technology is transformative, yet often truly challenging. There’s no question that Kubernetes has become the de-facto infrastructure for nearly any organization these days seeking to achieve business agility, developer autonomy and an internal structure that supports both the scale and simplicity required to maintain a full CI/CD and DevOps approach.
In part 1 of this series, we talked about zombie data and what it means for your observability architecture. In this post, we’ll talk more about how to handle all of it. How well can your organization handle the firehose of data it’s collecting? Yes, you have the ability to collect it, but chances are you don’t have the financial or human resources available to analyze all of it effectively.
Dashboards are not just tools for businesses and other organizations to monitor and respond to their data, but can be a method of storytelling. All of our data has the potential to be crafted into compelling narratives, which can easily be accomplished with the help of Dashboard Studio’s customizable formats and advanced visualization tools. We can take a series of disparate datasets and bring them together in one place if they share a common theme — in this case, Halloween.
We’ve reached the point where our ability to collect data has actually exceeded our ability to process it. Nowadays, it’s commonplace for organizations to have terabytes or even petabytes worth of data sitting in storage, waiting patiently for well-intentioned systems admins to eventually analyze it.
DevOps is an IT delivery concept that combines people, practices and tools with the shared goal of accelerating the development of applications and services. Adopting DevOps at enterprise level typically requires: The continuous development of DevOps practices, as well as other factors like the rapid pace of modern code changes, facilitates a need for DevOps monitoring: a set of tools and processes to support the entire software development lifecycle.
The real beauty of this modern, cloud-fueled, DevOps-driven world that we are living in is that it’s so highly composable. In so many ways, we’ve been freed from the limitations and structures of the previous annals of software and technology history to build things the way that we want to, and however we choose to do so.
Grafana Loki is Grafana Labs’ open source log aggregation system inspired by Prometheus. Loki is horizontally scalable, highly available, and multi-tenant. In addition, Grafana Cloud Logs is our fully managed, lightweight, and cost-effective log aggregation system based on Grafana Loki, with free and paid options for individuals, teams, and large enterprises.
Redis is an open-sourced, BSD 3 licensed, highly efficient in-memory data store. It is used widely in the industry because of its incredible performance and ease of use. It can easily be used as a distributed, in-memory key-value store, cache, or message broker. It can hold virtually any data structure, making it highly versatile. Redis was architectured and developed with speed in mind and designed to keep all the data in memory.
For any organization that stores, processes, or transmits cardholder data, monitoring can pose a particular set of challenges. The Payment Card Industry (PCI) Data Security Standard (DSS) dictates rigorous monitoring and data security requirements for the cardholder data environments (CDEs) of all merchants, service providers, and financial institutions.
Open source monitoring and observability tools can be found in production all over the world – whether they’re being used by startups or entire enterprise development teams. DevOps, ITOps, and other technical teams rely on tools like Prometheus, Grafana, OpenSearch, OpenTelemetry, Jaeger, Nagios, Zabbix, Graphite, InfluxDB, and others to monitor and troubleshoot their cloud environment.
Software monitoring, how does it work? “We paid for a bunch of tools but we don’t know what we should be looking at. There are tons of charts that don’t seem to mean anything!” If you talk to people about software monitoring you’ve inevitably heard something similar to this. With so many possible metrics it can feel like searching for a needle in a haystack. Even with curated dashboards there is inherent confusion about what is important.
Flexera’s State of the Cloud Report 2022 pointed out that significant cloud spending is wasted, a major issue that is getting more critical as cloud costs continue to rise. In the current macroeconomic conditions, companies focus on identifying ways to reduce spending. To effectively do that, we need to understand the pricing model. We can then work towards the challenges of cost monitoring, optimization, and forecasting.
Logz.io is one of Logz.io’s biggest customers. To handle the scale our customers demand, we must operate a high scale 24-7 environment with attention to performance and security. To accomplish this, we ingest large volumes of data into our service. As we continue to add new features and build out our new machine learning capabilities, we’ve incorporated new services and capabilities.
Development teams build modern applications using microservice architectures. Individual services are built and maintained by separate teams, and then these services are combined using container-based orchestrators to comprise a complete product offering. Microservices are a standard development method because they allow teams to iterate releases, providing ongoing new customer-facing features and bug fixes without needing to redeploy an entire platform or app.
In my work as a technical evangelist at Cribl, I regularly talk to companies seeing annual data growth of 45%, which is unsustainable given current data practices. How do you cost effectively manage this flood of data while generating business value from critical data assets?
For most organizations, GitHub is mission critical. Your GitHub repositories likely also contain some of your organization’s most sensitive data. GitHub provides tools to help you protect and govern this data, with tools such as audit logs, code scanning alerts, and secret scanning alerts. However, analyzing these logs and alerts through GitHub’s UI can be challenging. For example, looking for trends in your code scanning alerts over time through GitHub’s UI is just not possible.
Earlier this month I hosted the “Everything You’ve Heard About Observability is Wrong (Almost)” webinar– thanks to all of you who attended. I wanted to follow-up with the attendees as well as those who were not able to join. As promised, it wasn’t the same old Observability presentation that we have grown accustomed to you know, all marketing with little value.
Splunk and Amazon Web Services (AWS) are celebrating 10 years of strategic collaboration — an incredible milestone which demonstrates our commitment to teamwork, co-innovation and exceptional, data-driven outcomes for our joint customers.
Observability is the ability to see and understand the internal state of a system from its external outputs. Logs, Metrics, and Traces, collectively called observability data, are three external outputs widely considered to be three pillars of observability. Now more than ever, organizations of all sizes must employ the necessary processes and technologies to harness the power of their data and make it more actionable.
Logs are a critical aspect of any production workload, as they give you insight into what is happening in your system and tell you which components may be having issues. The traditional method of looking at logs involves basic Linux commands like tail, less, or sometimes cat.
Large organizations often rely on multiple monitoring tools, security platforms, and auditing systems to meet the diverse needs of their observability, security, engineering, and compliance teams. Because these teams may use the same logs for many different use cases—including detecting potential threats or breaches, troubleshooting errors, and gauging the effectiveness of new features—it can be difficult to effectively standardize and route data.
Whether you’re rushing to troubleshoot an incident or proactively performing a security audit, the trial-and-error process of searching through millions of logs for key information can be time-consuming and cumbersome. To help you quickly surface important details from large swaths of log data, Datadog’s Log Explorer allows you to search and filter your logs, create visualizations, as well as group your logs by fields, patterns, or transactions.
Today, Cribl is releasing The State of Security Data Management 2022 in collaboration with CITE Research. The report examines the challenges that enterprises are facing as they work to balance evolving business priorities with cyber threats. The report was conducted in September 2022 and surveyed 1,000 senior-level IT and security decision-makers. The survey found that, although most organizations are confident in their data management strategy, few believe it’s actually sustainable.
Arthur Conan Doyle's Sherlock Holmes famously said, "You see, but you do not observe." Collecting application logs exhaustively and interpreting them to support business objectives are two different things. Application logs, also called app logs, event logs, and audit trails, are automatically generated records of computational events in IT environments.
OpenTelemetry is an open source set of tools and standards that provide visibility into cloud-native applications. OpenTelemetry allows you to collect metrics, traces, and logs from applications written in many languages and export them to a backend of your choice.
Mobile devices have changed our world. They come with us everywhere and provide invaluable services. One nagging problem is how to get data out of your mobile device. Specifically, logging metrics and events can be a trial. Opening up a public-facing port, managing the log receivers, coding… Wouldn’t it be nice if this was simplified? This article will demonstrate how easy delivering logs can be using Cribl.Cloud and simple HTTP POSTs – for free.
With an exploding volume of data and systems comes the need for observability, or the ability to understand the internal states of a system from knowledge of its external outputs. As a result, observability data's importance is at an all-time high. Businesses spanning every industry use it in various ways to respond to issues, increase agility, mitigate risk, and ultimately provide better experiences for their users. It’s an incredibly valuable commodity.
It’s Cybersecurity Awareness Month, and in that spirit, we’re offering a number of tips and tricks small security operations center (SOC) teams can use. I started my career working as part of a small SOC team, and working with other security experts here at Logz.io, we’re happy to offer these to small SOC teams who can often use all the help they can get! In the last post, we talked about managing security talent and building processes.
One of the gratifying things about working at Cribl is receiving daily validation that we’re making customers’ lives easier, and solving their real problems. Every time someone tells us something like this, our hearts gladden, and a goat angel gets its wings: Numbers like those also translate into…numbers. When we surveyed customers in our most recent quarter, our CSAT (Customer SATisfaction) score was above 90%.
Organizations and their software delivery pipelines are continually exposed to growing cyberattack vectors. Coupled with the massive adoption of open source software, which now helps power nearly all of our public infrastructure and is highly prevalent in most proprietary software, businesses around the world are more vulnerable than ever. Today’s organizations need to be more vigilant in protecting their software development infrastructure and processes.
Monitoring IT infrastructure and services has always been an essential IT prerequisite. However, your IT monitoring system and security measures need to upgrade with an exponential increase in the number of remote users post-pandemic. For instance, consider this: At the end of a work day, you are notified that one of your critical services has gone down. But the problem is that five teams support different processes of that service.
This article will give you a quick overview of some of the key attributes you should know in order to get started with leveraging the OpenTelemetry collector for your next telemetry project. As an integral component of any project that involves distributed tracking, the OpenTelemetry Collector plays an important role. Simply put, it is helpful to know that the collector itself is a data pipeline service that collects telemetry data.
Over the last 15 years, digital technology has fundamentally changed the way businesses operate. Every industry, from retail and hospitality to banking and airlines, has not only had to adjust to a world where customers increasingly rely on digital experiences, but they also have to build and manage the platforms where these experiences take place.
One thing that adds value to a business’s ecommerce presence is the ability for customers to easily find physical stores with an interactive map. Store locators can be built quite rapidly — all you need to place them on a map is geographic location in latitude and longitude. In this post, I’ll outline the pieces needed to put together a proof-of-concept store locator that could later be added to an ecommerce website.
Moving to Splunk Cloud Platform has a lot of benefits, including flexibility, agility, and scalability. However, we understand that migrating to cloud is not a trivial task and can also bring up security concerns especially when it comes to having your data traverse the internet.
Observability is a methodology that you incorporate into your enterprise architecture to provide greater visibility into what is happening. It helps us determine the states of the system from their external outputs and allows technicians to identify bottlenecks, predict issues and mitigate them. As the architectures of IT systems are becoming more complex and distributed we use observability to meet the need to measure their internal states.
Observability is a hot topic in the IT world these days. It is oftentimes discussed through the lens of the “three pillars of observability”: Logs, Metrics and Traces. Indeed these telemetry signal types help us understand what happened, where it happened and why it happened in our system.
When we began the week, we had zero awards from Comparably. As we end the week, we now have a three-peat of awards. Cribl was recognized among 70,000 companies out of 15 million ratings – winning top honors for Happiest Employees, Best Compensation, and Best Perks and Benefits. We’re thrilled to be recognized by Comparably, and we’re looking forward to continuing our pursuit of being the best place to work.
Many developers don’t know what instrumentation really is, and those who do don’t really understand the black magic that takes an application and makes it emit telemetry, especially when automatic instrumentation is involved. On top of that, each programming language has its own tricks. I wanted to unwrap this loaded topic on my podcast, OpenObservability Talks. For this topic I invited Eden Federman, CTO of Keyval, a company focused on making observability simpler.
We all know that observability is a must-have for operating systems in production. But we often neglect our own backyard — our software release process. We noticed we made that mistake here at Logz.io. We were wasting time and energy in handling failures in the CI/CD pipeline, and made our Developer-on-Duty (DoD) shifts tedious. That’s why it’s critical to incorporate your observability practices into your CI/CD pipeline.
Building modern, cloud-native applications introduces new challenges to teams and organizations. As these systems grow and scale, struggles abound: inconsistent performance monitoring experiences across siloed tools, wasteful performance management practices with duplicated efforts, and mounting frustration from colleagues and customers. Surmounting these challenges requires multiple sources of data and truly unified observability.
Every security operations center (SOC) team is different, and for smaller teams, even small challenges can seem big. I started my career in cybersecurity as part of a smaller team, and eventually grew into a SOC role. During that time, I gained a good deal of knowledge about the dos and don’ts of what a small SOC team needs to do in order to be successful.
So, what is Universal Profiling™? Universal Profiling™ is fast emerging as an important component of observability. A standard feature inside hyperscalers since approximately 2010, the technology is slowly percolating into the wider industry. Universal Profiling™ allows you to see what your code is doing all the time, in production across a wide range of languages and can profile both user-space and kernel-space code.
The United States is the #1 target for cybersecurity attacks in the world. 38% of targeted cybersecurity attacks so far in 2022 were aimed at the United States data and systems. That’s alarming. And we see it in the news almost every day. Solarwinds, Colonial Pipeline, The Pulse Secure VPN zero-day… There’s an increasing number of threats and attacks, to the tune of 15.1% year over year.
From its inception as a powerhouse for logging, Elastic Observability has grown into a comprehensive solution for full-stack multi and hybrid-cloud observability. Given the increasing complexity of the cloud-native world, the major challenge for observability is twofold: getting deeper and more frictionless visibility at all levels of applications, services, and infrastructure, and making sense of the overwhelming amount of data that is available.
The Cambridge English Dictionary defines a silo as “a part of a company, organization, or system that does not communicate with, understand, or work well with other parts.” Siloing can exist at various organizational levels: siloed departments, siloed teams within a department, and even siloed engineers within a team. In any industry, siloing can cause issues with alignment, communications, and overall delivery, but in fintech, there are additional risks.
As Kubernetes monitoring continues to standardize on Prometheus as a form factor, more and more developers are becoming familiar with Prometheus’ built-in query language, PromQL. Besides being bundled with Prometheus, PromQL is popular for being a simple yet expressive language for querying time series data. It’s been fully adopted by the community, with lots of great query repositories, sample playbooks, and trainings for PromQL available online.
Every millisecond, humans generate significant volumes of data, from various IoT devices such as our wearable devices to daily activities such as internet surfing and tracking our workouts. Data continues to accumulate. Statista estimates that by 2025, the amount of data will have increased to 180 zettabytes. That's far too much information.
