Micro Lesson: Universal Connector
This video covers Sumo Logic’s new capability, Universal Connector and shows how to set up the source configuration.
Operations | Monitoring | ITSM | DevOps | Cloud
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The latest News and Information on Log Management, Log Analytics and related technologies.
Data Warehouse vs. Database: Differences Explained
If you're new to working with data, you might have heard of databases and data warehouses. But do you know what sets them apart? Knowing the differences between data warehouses and databases can clear up a lot of confusion for many people, especially with the volume of data we have these days. In this blog post, I'll discuss the differences between these two types of data systems. I'll also provide some examples to help illustrate the points made.
systemctl logs: A Guide to Managing Logs in Linux
Learn how to manage and view systemctl logs in Linux with this guide, covering essential commands and best practices for troubleshooting.
Python Logging with Structlog: A Comprehensive Guide
Master Python logging with structlog! Learn how structured logs improve debugging, observability, and performance in your apps.
Elastic vs Sumo Logic: Build vs buy the right logging platform
When it comes to logging tools, organizations often face a classic tech dilemma: build vs. buy. Should you invest in a robust, ready-to-use SaaS solution like Sumo Logic or dive into the customization rabbit hole with a PaaS option like Elastic? It's a debate as old as time—well, as old as software, anyway. Let's break it down in a way that actually makes sense, and hopefully, it’ll spark less drama than the pineapple-on-pizza debate.
Break down barriers to log collection with Sumo Logic's Universal Connector
Today’s dynamic multi-cloud ecosystems receive logs from countless sources. Relying on custom collectors and integrations can lead to tool sprawl, pipeline breakdowns, and time-consuming maintenance. Enter Sumo Logic’s Universal Connector, your streamlined solution for collecting logs from any source. With seamless API integrations, Universal Connector simplifies log collection and eliminates the overhead of building custom pipelines.
Incident Management for Software Engineers: Lessons from Production Fires
A notification "Critical: Payment processing down" is every software engineer's nightmare - a production incident that demands immediate attention. But the truth is that production incidents are inevitable. The question isn't whether they'll happen, but how well you'll respond when they do. In this article I explore the lessons I learned from real-world production fires.
Reducing Risk by Prioritizing Use Case Development
The session is really about customers spending their resources wisely, prioritizing use case development based on blind spots, weaknesses, or maybe even just plain audit findings. We have all been guilty in the past of spending a lot of time building clever use cases just for them to never fire or not work out the way we’d hoped; this talk is aimed at highlighting this issue and teach users to focus their resources and build a strategy for development like any other process they would internally.
About us - Sumo Logic
A log on its own is pretty simple, but they're rarely alone. Your digital applications, infrastructure and AI keep adding another, and another, and another… For some teams, this exponential data is overwhelming, causing friction, bottlenecks, and even tuning it all out. But at Sumo Logic, we’re FUELED by the atomic level of logs. The Sumo Logic Log Analytics Platform ingests each and every bit of this structured and unstructured “data exhaust,” transforming it into critical fuel for context-driven insights into your performance, availability, security status, and threats.
Is Your Telemetry Data Strategy Ready for the Next Decade?
What worked for the last 10 years won’t work for the next 10. IT and Security teams face three big challenges with telemetry data: Volume: Telemetry data is growing at a 28% CAGR, while budgets remain flat. Compliance requirements demand retaining massive datasets, straining both storage and costs. Variety: Logs, metrics, traces, configs—telemetry data comes in all shapes and sizes, making it difficult for traditional analytics tools to handle. Your tech needs to manage this complexity seamlessly.