Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

A pivotal inhibitor to mitigate these challenges is the Data Value Gap. Data automation and Data Fabric are emerging as key technologies to overcome these challenges. Learn from industry experts about these key technologies and how they create a lasting impact in enterprise IT.

With the advances in technology and an unpredictable macro environment, IT professionals have to deal with a deluge of data, increasing cyberthreats, distributed infrastructure and workforce, a mix of modern and monolithic apps and hybrid environments. Although there is significant momentum towards the Cloud, many organizations cannot move all of their data to the public cloud due to security, compliance or technical constraints.

Your organization purchased Splunk Cloud Platform some time ago. Your environment is ingesting dozens of data sources and your team has expert level SPL skills. You've created easily consumable dashboards and reports for many different types of stakeholders and you've mastered alert fatigue. Your organization's return on investment both in Splunk and Splunk education is paying large dividends in terms of time saved managing threats and improved operational efficiency.

There’s no question that the last 18 months have seen a pronounced increase in the sophistication of cyber threats. The technology industry is seeing a macro effect of global events propelling ransomware and wiperware development further into the future, rendering enterprise security systems useless. Here at Coralogix, we’re passionate about observability and security and what the former can do for the latter.

Digital-first businesses are striving for service assurance, which has become the lifeblood for their businesses processes. But they are increasingly getting complex across legacy and cloud-native applications, multi-cloud distributed services, with the rise of edge and when leveraged with Kubernetes and microservices architectures. Service assurance needs full-stack observability; however, customers need an approach to tame the data deluge while enabling actionable insights.

My market trends and predictions for 2021, be it for AI-based drug discovery or cybersecurity, have certainly accelerated in 2022 as a result of Covid-19 and the ongoing pandemic. This has brought unprecedented uncertainty, fear and challenges to how we do business, work, live and play.

Organizations today are pressured to keep their IT applications and infrastructure up and running and minimize their downtime. While this has always been a critical goal, it’s become harder to achieve with modern architectures, such as microservices, containerization, edge computing, hybrid-cloud deployments and the newer development methods such as agile DevOps techniques.

Enterprise data systems are like busy family households. You see a constant flow of activity to varying degrees from room to room. This activity includes people wandering, opening and closing doors. And then there are other streams constantly flowing through the household- electricity, water, Wi-Fi networks and more. In modern enterprises, the data deluge is a critical issue. While we take the complexity for granted in a household, such is not allowed in a connected enterprise.

The rise of cloud native and containerization, along with the automation of the CI/CD pipeline, introduced fundamental changes to existing application development, deployment, and security paradigms. Because cloud native is so different from traditional architectures, both in how workloads are developed and how they need to be secured, there is a need to rethink our approach to security in these environments.

Observability (logs, traces, metrics) is a core tenet to building strong software systems. Logs are used to debug issues and check on system activity, traces provide valuable insights into system performance and architecture, and metrics allow engineering teams to closely track business metrics within their systems.