The popularity of serverless architectures continues to grow as organizations seek ease of scalability and to eliminate the need to provision and manage infrastructure. In fact, in our most recent State of Serverless report, we found that more than half of our customers have adopted serverless technologies offered by Azure, Google Cloud, and AWS.
Just like shopping on Black Friday, AWS re:Invent has become a post-Thanksgiving tradition for some of us at Datadog. We were excited to join tens of thousands of fellow AWS users and partners for this annual gathering that features new product announcements, technical sessions, networking, and fun. This year, we saw three themes emerge from the conference announcements and sessions.
With the continual increase of attacks, vulnerabilities, and misconfigurations, today’s security organizations face an uphill battle in securing their cloud environments. These risks often materialize into unaddressed alerts, incidents, and findings in their security products. However, part of the issue is that many security teams are often stretched too thin and overburdened by alert fatigue.
With the continual increase of attacks, vulnerabilities, and misconfigurations, today’s security organizations face an uphill battle in securing their cloud environments. These risks often materialize into unaddressed alerts, incidents, and findings in their security products. However, part of the issue is that many security teams are often stretched too thin and overburdened by alert fatigue.
Amazon Security Lake allows customers to build security data lakes from integrated cloud and on-premises data sources as well as from their private applications. Directing your security telemetry into a unified data lake makes it easier to manage, analyze, and route security-log and event data to third-party SIEM solutions that leverage that telemetry.
Investigating the origin of activity in cloud-native infrastructure—and understanding which activity is a potential threat—can be a challenging, time-consuming task for organizations. Cloud environments are complex by nature, comprising thousands of ephemeral, interconnected resources that generate large volumes of alerts, logs, metrics, and other data at any given time.
Editor’s note: This is Part 2 of a five-part cloud security series that will cover protecting an organization’s network perimeter, endpoints, application code, sensitive data, and service and user accounts from threats.
OAuth is an authorization protocol that allows apps to securely request user data without requiring the user to enter their sensitive credentials (e.g., API keys, application keys, etc.). Datadog API-based data integrations now fully support OAuth.
Organizations are rapidly migrating their infrastructure to the cloud, enabling them to modernize their applications and deliver more value to their customers. But this transition creates significant security risks that they may be unable to keep pace with. For example, cyber attacks on cloud resources are becoming more sophisticated and prevalent. Additionally, organizations often rely on legacy, disjointed security tools that don’t integrate well with cloud-native infrastructure.
In the cloud, securing identities and workloads is both paramount and complex. Inventories of AWS customer security breaches help us learn from publicly disclosed incidents—but until now, not much concrete data has been shared around the usage of security mechanisms that could have helped prevent these incidents. For this report, we examined real-world data from a sample of more than 600 organizations and thousands of AWS accounts that use the Datadog Cloud Security Platform.
