We're excited to announce that indices created in Elasticsearch 7.10 will be smaller. Bigger isn't always better, and our internal benchmarks reported space reductions up to 10%. This may not seem like much for small use cases, but it's huge for teams handling (and paying for cloud storage of) petabytes of data.
Gartner recently released their top strategic technology trends for 2021. It’s no surprise that these trends reflect what many of us and our organizations have been experiencing, dealing with ongoing challenges during this global pandemic.
The concept of a microservice perfectly fits the structure of a serverless function, which easily enables deployment and runtime isolation for different services. On the storage side, services such as DynamoDB also make it easier to have independent databases for each microservice and scale them independently (when required or desirable). Before we dive into details, please consider whether the benefits of Microservices abundantly outweigh its disadvantages for your particular project and team.
This short guide for conducting successful big data analysis will take you through a couple of the most essential tips to help you learn how to analyse data & become a better data analyst by avoiding rookie mistakes and embracing the correct mindset to get the most from your data. We’ll also cover some of ways that conducting effective data analysis can help your organisation.
With an ever growing list of infrastructure improvements, new features, and issues to debug, setting up your observability tools to keep up with best practices can fall down your list of priorities. There’s simply not enough time to set up new dashboards that can give you the visibility you need to be proactive with your infrastructure.
It’s budgeting season for many of us. As a result, capacity planning and cost justification for hardware purchases are likely on your mind. But don’t fear, because Galileo has you covered. We’ve curated a bunch of our most popular and helpful resources for your capacity planning project, and they’re all here in one handy place.
Today, AWS has announced AWS Network Firewall: a new managed service that makes it easy to deploy essential network protections for Amazon Virtual Private Clouds (VPCs). As a launch partner, Splunk has worked closely with AWS to provide customers an integration to AWS Network Firewall. In today’s blog, co-authored by my esteemed colleague Anush Jayaraman, we’ll first detail the data flow architecture and your options to ingest the AWS Network Firewall data.
When you take a close look at the Continuous Diagnostics and Mitigation (CDM) function at the heart of a successful cybersecurity program, you quickly realize that it all depends on integration. It isn’t that the individual components of the program aren’t absolutely essential. But with cyber-attacks gaining in number and sophistication, the true power of CDM is in the ability to overlay multiple datasets to create a single lens for tracking, assessing, and responding to threats.
Problem: If there are thousands of employees scattered around hundreds of places, how do you keep your organization’s network safe? Solution: You should monitor your employees wherever they’re located, and devise a standard baseline of their behavior through machine learning techniques. By using that information, you can identify anomalies and protect your network from cyberattacks.
Oracle Cloud Infrastructure (OCI) is an infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) cloud used by enterprise-scale companies. With a full suite of services for hosting, storage, networking and more, OCI lets customers deliver, maintain, and scale secure, highly available applications. But as your cloud infrastructure becomes more complex, monitoring the full scope of activity across your services and accounts can be increasingly difficult.
