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Dynatrace elevates data security with separated storage and unique encryption keys for each tenant

Dynatrace

Enhancing data separation by partitioning each customer’s data on the storage level and encrypting it with a unique encryption key adds an additional layer of protection against unauthorized data access. A unique encryption key is applied to each tenant’s storage and automatically rotated every 365 days.

Storage 246
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Cut costs and complexity: 5 strategies for reducing tool sprawl with Dynatrace

Dynatrace

As an executive, I am always seeking simplicity and efficiency to make sure the architecture of the business is as streamlined as possible. Simplify data ingestion and up-level storage for better, faster querying : With Dynatrace, petabytes of data are always hot for real-time insights, at a cold cost.

Strategy 262
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New continuous compliance requirements drive the need to converge observability and security

Dynatrace

Leverage AI for proactive protection: AI and contextual analytics are game changers, automating the detection, prevention, and response to threats in real time. UMELT are kept cost-effectively in a massive parallel processing data lakehouse, enabling contextual analytics at petabyte scale, fast.

Analytics 289
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What is security analytics?

Dynatrace

As a result, organizations are implementing security analytics to manage risk and improve DevSecOps efficiency. Fortunately, CISOs can use security analytics to improve visibility of complex environments and enable proactive protection. What is security analytics? Why is security analytics important? Here’s how.

Analytics 264
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Unlock the power of contextual log analytics

Dynatrace

This is explained in detail in our blog post, Unlock log analytics: Seamless insights without writing queries. There is no need to think about schema and indexes, re-hydration, or hot/cold storage. Using patent-pending high ingest stream-processing technologies, OpenPipeline currently optimizes data for Dynatrace analytics and AI at 0.5

Analytics 304
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RabbitMQ vs. Kafka: Key Differences

Scalegrid

This article outlines the key differences in architecture, performance, and use cases to help determine the best fit for your workload. Kafka is optimized for high-throughput event streaming , excelling in real-time analytics and large-scale data ingestion. What is RabbitMQ? What is Apache Kafka?

Latency 147
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Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes.

Analytics 264