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Do High Storage Costs Put Success of Splunk Acquisition at Risk?

2023 was a big year for observability acquisitions—but storage costs too much for big data, including AI training use cases.

Hydrolix Staff

Published:

Jan 08, 2024

2 minute read

Observability is a hot commodity right now. In 2023, there were five major acquisitions in the observability space, including Splunk, Sumo Logic, and New Relic. As Hydrolix CEO and co-founder Marty Kagan writes in insideBigData:

“The aim is clear: use the data these companies collect to fuel the next big wave of AI-powered operations and security tools.”

Despite the opportunities that AI-powered observability will provide, there are a number of challenges that the observability sector must solve in order to successfully harness AI.

The biggest challenge: AI is data-hungry, but current data storage architectures are too expensive, making it difficult to store data long-term. If the problem isn’t solved, the acquisitions of 2023 could turn into financial headaches in 2024 and beyond. In order to solve the problem, the insideBigData piece argues that: 

“Hot storage costs need to be much closer to raw object storage to serve the AI ambitions of companies like Cisco, Dell, and HPE. Architectures are emerging that decouple storage, allowing compute and storage to scale independently, and index that data so that it can be searched quickly. This provides solid-state drive-like query performance at near object storage prices.”

If the problem of data storage costs isn’t addressed, can current observability solutions deliver the data AI training pipelines need? We firmly believe that the answer is no.

Hydrolix Makes Data Cost-Effective at Scale

Hydrolix is purpose-built to ingest, analyze, and store data at the scale that modern enterprises need, including observability and AI-driven platforms—at a fraction of the cost of traditional solutions. With Hydrolix, you can reduce your costs by 75% or more and keep all data in the hot storage tier. Learn more about Hydrolix features like decoupled compute and storage, advanced compression techniques, and indexing. 

Learn more about Hydrolix and contact us for a POC.

Read the insideBigData article: To Make the Splunk Acquisition Successful, a New Approach to Storage is Needed.

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Observability is a hot commodity right now. In 2023, there were five major acquisitions in the observability space, including Splunk, Sumo Logic, and New Relic. As Hydrolix CEO and co-founder Marty Kagan writes in insideBigData:

“The aim is clear: use the data these companies collect to fuel the next big wave of AI-powered operations and security tools.”

Despite the opportunities that AI-powered observability will provide, there are a number of challenges that the observability sector must solve in order to successfully harness AI.

The biggest challenge: AI is data-hungry, but current data storage architectures are too expensive, making it difficult to store data long-term. If the problem isn’t solved, the acquisitions of 2023 could turn into financial headaches in 2024 and beyond. In order to solve the problem, the insideBigData piece argues that: 

“Hot storage costs need to be much closer to raw object storage to serve the AI ambitions of companies like Cisco, Dell, and HPE. Architectures are emerging that decouple storage, allowing compute and storage to scale independently, and index that data so that it can be searched quickly. This provides solid-state drive-like query performance at near object storage prices.”

If the problem of data storage costs isn’t addressed, can current observability solutions deliver the data AI training pipelines need? We firmly believe that the answer is no.

Hydrolix Makes Data Cost-Effective at Scale

Hydrolix is purpose-built to ingest, analyze, and store data at the scale that modern enterprises need, including observability and AI-driven platforms—at a fraction of the cost of traditional solutions. With Hydrolix, you can reduce your costs by 75% or more and keep all data in the hot storage tier. Learn more about Hydrolix features like decoupled compute and storage, advanced compression techniques, and indexing. 

Learn more about Hydrolix and contact us for a POC.

Read the insideBigData article: To Make the Splunk Acquisition Successful, a New Approach to Storage is Needed.