DevOps と IT 業務｜リソースセンター

Imagine you are an on-call engineer, who receives an alert at 3 AM in the morning informing you that customers are experiencing high latency on your website, and are unable to shop.

HAProxy is one of the fastest and most widely-used load balancing solutions available today. If you’re already using HAProxy, or if you’re considering using HAProxy in your environment, then this is a great place to start. On this page, we discuss HAProxy logging and why logging is such a vital component of the load balancer implementation. We then take a deep dive into the logging offered by HAProxy. Finally, you’ll read about working with the HAProxy logging format and how you can configure the logging to suit your needs better.

Sumo Logic is excited to announce that it has achieved the New York State Department of Financial Services Attestation to support our customers’ abilities to meet privacy and security requirements for critical data.

As part of the move to the cloud, everything in the enterprise is being transformed—from infrastructure all the way to modern application development. Nowhere is this change more important than in the role of the CISO.

In this article, we will explain the basic characteristics of Redis, MongoDB, and Cassandra databases. In addition, we will show you how to collect and monitor the logs that these databases produce using Sumo Logic’s unified logs and metrics (ULM) offering and related apps.

HAProxy is one of the world’s most innovative and highest-performing load balancing solutions. The load balancer is critical for enabling high availability and supporting the dynamic scaling of infrastructure within modern applications. Because of its importance, engineers need tools that can quickly and effectively diagnose any problems with the load balancer if they arise.

Red Hat OpenShift is an open source container application platform that incorporates a collection of software that enables developers the ability to run an entire Kubernetes environment. It includes streamlined workflows to help teams get to production faster and is tested with dozens of technologies while providing a robust tightly-integrated platform supported over a 9-year lifecycle.

We all know how our life has changed in the last two decades in terms of how we interact with our vendors for day to day activities, regardless if we shop for a birthday present or read a newspaper. This digital transformation of everything we do increased even more during the pandemic, when it appeared that a malfunctioning digital access channel can often mean lack of possibility to enter certain places like even the country or a plane to get back home.

What better way is there to get insight into your app performance than by leveraging the traffic management tools connecting your apps to your customers? With Sumo Logic and NGINX, you can easily get information on the health of your apps and save valuable time.

In this blog, we will show you some simple steps for deploying and running a PostgreSQL database on Kubernetes. We will explore a simple use case in which a developer wants to have a single PostgreSQL instance for testing, and then we’ll introduce an advanced use case in which there are a few options for deploying a more configurable instance of PostgreSQL.

In the era of data abundance, there exists a significant need for database systems that can effectively manage large quantities of data. For certain types of applications, an oft-considered option is Apache Cassandra. Like any other piece of software, however, Cassandra has issues that could potentially impact performance. When this happens, it’s critical to know where to look and what to look for in the effort to quickly restore service to an acceptable level.

With a multitude of digital options available in almost every industry, it’s become increasingly critical that applications and services provide a positive user experience. Doing so requires a high level of availability, made possible (in part) by efficiently identifying and resolving issues with the system, when they occur.

In one of my previous blogs I explained how important it is for a modern observability platform to provide “the observers” full, flexible access to all raw telemetry. Observability’s promise to find unknown unknowns relied directly on the ability of fast, powerful and multidimensional high-cardinality analysis of raw data, to uncover previously unknown patterns that have not yet been visualized as a metric, dashboard panel or an alert or anomaly event.

In this article we look at how to monitor Cassandra database clusters. We start with the basic architecture of a Cassandra cluster, and mention the most important metrics to gather. Next, we advance step-by-step into configuring and setting up a monitoring stack with Jolokia, Telegraf and Sumo Logic collectors and dashboards – everything you need to monitor Cassandra databases.

Many of our customers today leverage Office 365 GCC High, including organizations looking to meet evolving requirements for working with the United States Department of Defense. Sumo Logic enables customers to leverage our out-of-the-box monitoring and analytics capabilities to analyze Office 365 GCC High data to offer security engineers and security analysts stronger situational awareness of internal employee data.

A common scenario for log analytics is that many log events are high value for real time analytics, but there are also events that are low value for analytics, but account for a very large percentage of overall log volume.

The Sumo Logic team is excited to announce that it has been named a Visionary in the Gartner 2021 Magic Quadrant for Security Information Event Management (SIEM). We believe our placement in the Visionary quadrant reflects the value and success our customers have realized by using our cloud-native security platform and the innovative ways in which it solves SIEM and modern security operations use cases.

In this article, we're going to focus on pillar number five: measuring everything. We'll discuss five key metrics for DevOps software pipelines and explain how each of them can help measure software delivery performance.