Splunk Mission Control attempts to reinvent security operations, it’s a unified security operations platform that brings together security data, analytics, and operations under one umbrella.
Splunk offers an expansive processing language that enables a user to be able to reduce and transform large amounts of data from a dataset, into specific and relevant pieces of information.
While developing Splunk apps and add-ons, we rely heavily on Python for various third-party integrations. Even though tested, Sometimes we run into issues when the code actually gets executed inside Splunk’s Python environment.
For large Splunk Deployments, we often get asked the questions on how to centrally monitor the platforms. The problem in light is for the Monitoring of Monitoring.
A single instance deployment is often a good approach for testing and POCs. It might even work for smaller environments as it handles all aspects of Splunk including indexing and search.
We as a Splunk admin, receive multiple onboarding requests. These can be from various data sources which may include API data or any cloud data.
Splunk has built powerful capabilities to extract the data from JSON and provide the keys into field names and JSON key-values for those fields for making JSON key-value (KV) pair accessible.
Crest Data Systems being one of the largest Enterprise Integrations provider in the world in the areas of Data Analytics and Cybersecurity has helped several small and large Enterprises build rich integrations across their IT Ops and Security infrastructure.
AWS GuardDuty is a managed threat detection service that continuously monitors for malicious or unauthorised behaviour to help you protect your AWS accounts and workloads.
Splunk is an incredibly robust tool that can scale depending on the certain parameters: Number of users using the deployment, Amount of data coming in, Number of endpoints sending data to the deployment.
