Operations | Monitoring | ITSM | DevOps | Cloud

Log data is the most fundamental information unit in our XOps world. It provides a record of every important event. Modern log analysis tools help centralize these logs across all our systems. Log analytics helps engineers understand system behavior, enabling them to search for and pinpoint problems. These tools offer dashboarding capabilities and high-level metrics for system health. Additionally, they can alert us when problems arise.

A data lake is the perfect solution for storing and accessing your data, and enabling data analytics at scale - but do you know how to make the most of your AWS data lake? In this week’s blog post, we’re offering 10 data lake best practices that can help you optimize your AWS S3 data lake set-up and data management workflows, decrease time-to-insights, reduce costs, and get the most value from your AWS data lake deployment.

While log parsing isn’t very sexy and never gets much credit, it is fundamental to productive and centralized log analysis. Log parsing extracts information in your logs and organizes them into fields. Without well-structured fields in your logs, searching and visualizing your log data is near impossible.

In today’s digital-first world, most security problems are actually data problems, and data volumes are outpacing organizations’ abilities to handle, process, and get value from it. You’ll have 250% more data in five years than you have today, but the chances of your budget increasing to match that are slim. The challenges that come with managing the rise in enterprise data volume directly affect your ability to adequately address cybersecurity risks.

Are you prepared for the unexpected? In today's rapidly evolving world, operational resilience has never been more critical for businesses to survive and thrive. Resiliency is the ability of a system to maintain its operations under adverse conditions, including system failures, unexpected surges in user demand, or even security breaches. The heart of many applications, particularly in this era of data-driven decision-making, is the data store or database.

The Open System Interconnection model (OSI Model) is a foundational concept that shapes how we build digital environments. The OSI Model is a conceptual framework that describes how different computer systems communicate with each other inside network or cloud/internet environments. Today, let’s look at how the OSI Model affects our digital lives, applications and networks.

When our CEO and co-founder Tomer Levy delivered his “Observability is Broken” presentation at last year’s AWS re:Invent, he highlighted numerous challenges faced by today’s organizations as they seek to advance their observability practices. Of the six individual points that he noted, two specifically dealt with the current shortage of available engineering expertise, with another two focused on data overload.

Cribl Search is a powerful tool that is designed to enhance your data search efficiency, irrespective of the location of your data. This blog will explore how this tool seamlessly integrates with numerous Cribl Edge Nodes in real time, simplifying the process of discovery and troubleshooting. An integral part of Cribl Search is the “teleport” feature, which enables users to access specific Edge Nodes for in-depth analysis, simply by clicking on a host field.

Technology juggernauts–despite their larger staffs and budgets–still face the “cognitive load” for DevOps that many organizations deal with day-to-day. That’s what led Spotify to build Backstage, which supports DevOps and platform engineering practices for the creation of developer portals.