Operations | Monitoring | ITSM | DevOps | Cloud

How to mitigate the challenges of data growth

Over the last decade, I’ve rarely met a data professional whose organization wasn’t experiencing data growth and making more demands of their data. We build and deploy new applications faster than we retire old ones, and new data is accumulating dramatically faster on our existing systems than our ability to decide to delete older information. Additionally, the ever-growing number of users and devices interacting with that data increases the strain on the infrastructure underpinning it.

The Pleasure of Finding Things Out: Federated Search Across All Major Cloud Providers and Native Support for Amazon Security Lake

The newly released Cribl Search 4.2 brings enhancements that ease data management in today’s complex, cloud-centric environments. This update provides comprehensive compatibility with all major cloud providers – Amazon S3, Google Cloud Storage, and Azure Blob Storage. It also ushers in native support for Amazon Security Lake. In this blog post, we’ll examine how new dataset providers enhance the value that Cribl Search delivers, out of the box.

The Benefits of Business Monitoring in the Gaming Industry: Enhancing Savings, User Experience, and Performance

The gaming industry has always been a highly lucrative and adored field. According to online gaming industry statistics, it is projected to surpass $33.77 billion by 2026. However, a downside emerges when governments impose substantial taxes on the income generated from gaming. It’s happening now. The Indian government has decided to impose a 28% tax on online gaming, which may lead to a funding shortage and a decrease in investor confidence.

InfluxDB 3.0 is up to 45x Faster for Recent Data Compared to InfluxDB Open Source

With the release of InfluxDB 3.0, one of the big questions is: how does it compare to previous versions of InfluxDB? We have begun benchmarking InfluxDB 3.0 with production workloads to start giving users more insight into the benefits of adopting InfluxDB 3.0. In this post, we look at recent benchmarks comparing InfluxDB 3.0 to InfluxDB Open Source (OSS) 1.8.

Getting Started with Users in pgAdmin and Aiven

In this tutorial, we'll walk you through the process of creating users both on pgAdmin, a powerful GUI tool for managing PostgreSQL databases, and the Aiven platform. User management is an essential aspect of database administration, and we'll show you how to add new users, define their roles and privileges, and configure authentication settings. Whether you're a beginner or an experienced user, this video provides a comprehensive guide to effectively create and manage users in your PostgreSQL environment.

Don't Drown in Your Data - Why you don't need a Data Lake

As a leader in Security Analytics, we at Elastic are often asked for our recommendations for architectures for long-term data analysis. And more often than not, the concept of Limitless Data is a novel idea. Other security analytics vendors, struggling to support long-term data retention and analysis, are perpetuating a myth that organizations have no option but to deploy a slow and unwieldy data lake (or swamp) to store data for long periods of time. Let’s bust this myth.

Dark Data: Discovery, Uses, and Benefits of Hidden Data

Dark data is all of the unused, unknown and untapped data across an organization. This data is generated as a result of users’ daily interactions online with countless devices and systems — everything from machine data to server log files to unstructured data derived from social media. Organizations may consider this data too old to provide value, incomplete or redundant, or limited by a format that can’t be accessed with available tools.

Data Lakes Explored: Benefits, Challenges, and Best Practices

A data lake is a data repository for terabytes or petabytes of raw data stored in its original format. The data can originate from a variety of data sources: IoT and sensor data, a simple file, or a binary large object (BLOB) such as a video, audio, image or multimedia file. Any manipulation of the data — to put it into a data pipeline and make it usable — is done when the data is extracted from the data lake.