Observability is a growing practice that provides many benefits to IT and DevOps teams. With greater visibility into their environments, teams can determine the state of the system, predict issues, and mitigate them before end users are impacted. Observability makes data more usable and in turn, businesses reap the benefits of having great insights.
Are you on the fence on whether to get started with your own observability practice? Check out these 12 observability benefits and get started today!
We live in a digital world and the amount of data that gets generated every day is only increasing. Teams are drowning in massive amounts of data, struggling to get a grasp of it all and make it make sense. This is only getting harder as new tools and capabilities are added to the stack. Observability gives back control — control everything from how data is delivered, what format it’s in, and where it should be forwarded to. Decouple the data ingestion layer from data analytics tools to reduce complexity and tool dependencies.
The three pillars of observability data are logs, metrics, and traces. Each of these generates data in different shapes and forms — structured, unstructured and semi-structured. To help simplify data collection, an observability pipeline acts as a universal receiver. It receives and processes data from all existing agents, and gives access to viewing all data flows and multiple parallel systems. The pipeline allows data to be ingested so teams can easily get value from it in any format, from any source, and then direct it to any destination.
An observability pipeline allows engineers to easily identify potential infrastructure and application issues and mitigate them quickly. Engineers can correlate multiple system data flows with a streamlined approach and reduce MTTD (mean time to detect). The systems can also be set to self-heal and queue data with different data pipeline infrastructures so data is never lost.
When an issue occurs, a monitoring tool will tell you where the issue is. An observability tool takes it a step further by monitoring trends, getting ahead of issues, and letting you know before something goes down. The power of observability is that it proactively tracks how systems perform, and can predict and prevent similar issues from occurring again in the future. An observability pipeline opens doors to new possibilities by allowing you to ask questions of your data that you didn’t even know you needed to ask beforehand.
See. It. ALL. Observability offers panoramic views into all data so that anyone within an organization — with the right access controls and data governance and compliance rules in place — can view. When IT and DevOps teams have easy access and real-time visibility to the data they need, they’re able streamline release cycles and optimize for better user experiences.
In an ideal world, you’d be able to retain all your data long term, and access it whenever you need. But the reality is, it’s crazy expensive to store data. Observability makes it possible to move low-value data from systems of analysis to low-cost cold storage, with the option to quickly replay the data back when needed. This allows for the best of both worlds — for data to be stored in a cost-effective manner while still optimized without additional compliance or regulatory concerns. Implementing an observability pipeline allows teams to store data in one sphere from which they can choose only the data they need for analysis, and move it to their analytics tool.
In today’s world, analyzing observability and security data at rest requires one or more commercial tools or SaaS services. Once you put data into your logging tools and services, this data is no longer your data — it’s the vendor’s data. Reading that data back requires maintaining a commercial relationship with the vendor, often with little leverage or control over the cost. The observability lake frees you from this lock-in and ensures the enterprise’s data always remains the enterprise’s data. With a replay capability, you’re able to easily take data in your lake and send it back to any of your existing solutions.
How do vendor-neutral data lakes work? You input information in their raw formats and process them through an analysis system of choice. But they are often resting and unreachable. Observability pipelines are the collectors that make the concept of a data lake possibly. They can reach out to cheap object storage like a data lake and bring it back to the front of the pipeline. It collects resting data, brings it back, and processes it in new ways. This data is replayed through the organizational systems as needed in the event that more analysis is needed.
Data governance and security are integral in any organization. There’s a huge liability working with sensitive data, and security teams need to ensure systems are properly secured. Observability tools allow you to easily create a centralized observability pipeline built with data governance principles. You only need to put the guidelines in once, and those automatically apply to multiple checkpoints. An observability pipeline also configures data streams for maximum protection. Redaction and masking keep sensitive data private. You want to protect your customers and limit liability, and it’s easy to do just that with an observability pipeline.
Traditional systems weren’t always engineered to provide useful information. That’s where the magic of observability comes in. Observability can be used to extract answers from even the oldest systems. Each stack is made up of all different tools and systems, organizations with distributed systems need them to work cohesively, despite what legacy tools may be in place. New, complementary observability tools are able to provide real-time data, easy scalability, and holistic visibility. With observability, teams can capture blind spot areas and create the best, most optimal infrastructure.
Security breaches can be detrimental to the business. Not only do breaches cost millions in damages, but it can ruin a company’s reputation and hurt customer trust. Being able to foresee a data breach can save organizations from heartache, expenses, and long-term damages. Observability tools can let teams know well in advance if there’s a threat on the horizon, and help teams get ahead of it before it’s too late.
Moving data to where it needs to be is no easy feat. You’re often dealing with multiple data sources, multiple tools, and the data is in all different formats. Open source tools require burdensome management and the hidden costs can pile on. Establishing an observability pipeline can help you easily collect, reduce, shape, enrich and route data to any destination, without adding new agents. The pipeline can reach out to any data at rest and connect any source to any destination.
Being able to work with data in real time means the data is immediately available and reaches the right teams as soon as it’s created. This is extremely powerful because teams can turn real-time data into real-time analytics, then make decisions in the moment that influence end users. For instance, an ecommerce site can let shoppers know in real time how much inventory is left. Or a bank customer can get alerted as soon as there’s fraud detected on their credit card. Having real-time data readily available gives greater visibility into how systems are performing, and having immediate insights can drastically improve customer experiences, and also help the business better manage inventory and improve operations.
Cribl Stream is a vendor-agnostic observability pipeline that gives customers flexibility to route and process data at scale from any source to any destination within their data infrastructure. With extensive experience building and deploying log analytics and observability solutions for some of the world’s largest organizations, Cribl helps customers take control of their data to support their business goals. Contact Cribl today!