Vaughn Stewart, VP of Technology Alliances, Pure Storage & Bharath Aleti, Director Product Management, Splunk, sit with Lisa Martin & Dave Vellante at Pure Accelerate 2019 in Austin, TX.
#PureAccelerate #theCUBE
https://siliconangle.com/2019/10/02/qa-pure-storage-and-splunk-smartstore-split-storage-and-compute-for-cloud-era-scalability-pureaccelerate/
Q&A: Pure Storage and Splunk SmartStore split storage and compute for cloud-era scalability
Storage and compute have been inseparable since the dawn of the database. Originally linked to reduce latency for transactional databases, the computing world has since moved beyond the demands of transactional processing. With today’s scalable architecture, tightly coupling storage and compute negatively impacts speed and availability — and increases costs.
“If you look at the demand today, we can see that the demand for storage is all based in the demand for compute,” said Bharath Aleti (pictured, right), director of product management at Splunk Inc. “[So] if we need to provide performance at scale, there needs to be a better solution than what we have right now.”
Aleti and Vaughn Stewart (pictured, left), vice president of technology alliances at Pure Storage Inc., spoke with Dave Vellante (@dvellante) and Lisa Martin (@LisaMartinTV), co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the Pure//Accelerate event in Austin, Texas. They discussed the relationship between Splunk and Pure and the benefits of Splunk SmartStore (see the full interview with transcript here). (* Disclosure below.)
[Editor’s note: The following answers have been condensed for clarity.]
Martin: Let’s start by talking about this Splunk-Pure relationship. Long relationship, new offerings, joint value, what’s going on?
Stewart: So, Splunk and Pure have had a long relationship around accelerating customer’s analytics, the speed at which they can get their questions answered, the rate at which they can ingest data … to be able to ingest more sources, look at more data, get faster time to take action. Splunk has released a new architecture, a significant evolution from the traditional Splunk architecture. [It’s] disaggregated based off caching and an object store construct called SmartStore.
Martin: Tell us more about Splunk’s SmartStore.
Aleti: What SmartStore brings to the table is that it decouples compute and storage. So now you can scale storage independent of compute. We broke the paradigm of compute and storage co-location and added a small twist: We bring compute and storage closer together only on demand. So, that means when we are running a query or we know we are running a search, and whenever the data is being looked for, that is only when we bring the data together.
The other key thing that we do is we have an active data set. We ensure that SmartStore has a very powerful cache manager that ensures that the active data set is always in the cache — very similar to the RAM on your laptop. The RAM on your laptop has active data sets always in the cache, always on memory. So [that’s] very similar to that SmartStore cache, [which] allows you to have your active data set always locally on the indexer so that your search performance is not impacted.
The SmartStore feature is already available on-premises. We are also already using it to host all of our Splunk cloud deployments as well, and it’s available for customers who want to deploy Splunk on AWS.
Vellante: How does Pure Storage fit with SmartStore?
Stewart: Where we come in relative to SmartStore is we were a co-developer, a launch partner. And because our object offering FlashBlade is a high-performance object store, we are a little bit different than the rest of the Splunk S3 partner ecosystem who have invested in slow, more of an archive-mode of S3. We have always been designed, and betting on the future would be based on high-performance large-scale object [storage]. And so we believe SmartStore is a perfect example of a modern analytics platform.
We’ve done comparison tests with other SmartStore search results that have been published in other vendors’ white papers, and we show FlashBlade, when we run the same benchmark, is 80 times faster.
So, what you can now have with that architecture is confidence. Should you find yourself in a compliance or regulatory issue, something like [General Data Protection Regulation], where you’ve got 72 hours to notify everyone who’s been impacted by a breach [or] any time where you’ve got to go back into history, we’re going to deliver those results faster than any other object store in the market today.
Martin: Does Splunk consider what FlashBlade is doing here an accelerant of Splunk workloads in customer environments?
...
(* Disclosure: TheCUBE is a paid media partner for the Pure//Accelerate event. Neither Pure Storage Inc., the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
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Vaughn Stewart, Pure Storage & Bharath Aleti, Splunk | Pure Accelerate 2019
Vaughn Stewart, VP of Technology Alliances, Pure Storage & Bharath Aleti, Director Product Management, Splunk, sit with Lisa Martin & Dave Vellante at Pure Accelerate 2019 in Austin, TX.
#PureAccelerate #theCUBE
https://siliconangle.com/2019/10/02/qa-pure-storage-and-splunk-smartstore-split-storage-and-compute-for-cloud-era-scalability-pureaccelerate/
Q&A: Pure Storage and Splunk SmartStore split storage and compute for cloud-era scalability
Storage and compute have been inseparable since the dawn of the database. Originally linked to reduce latency for transactional databases, the computing world has since moved beyond the demands of transactional processing. With today’s scalable architecture, tightly coupling storage and compute negatively impacts speed and availability — and increases costs.
“If you look at the demand today, we can see that the demand for storage is all based in the demand for compute,” said Bharath Aleti (pictured, right), director of product management at Splunk Inc. “[So] if we need to provide performance at scale, there needs to be a better solution than what we have right now.”
Aleti and Vaughn Stewart (pictured, left), vice president of technology alliances at Pure Storage Inc., spoke with Dave Vellante (@dvellante) and Lisa Martin (@LisaMartinTV), co-hosts of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, during the Pure//Accelerate event in Austin, Texas. They discussed the relationship between Splunk and Pure and the benefits of Splunk SmartStore (see the full interview with transcript here). (* Disclosure below.)
[Editor’s note: The following answers have been condensed for clarity.]
Martin: Let’s start by talking about this Splunk-Pure relationship. Long relationship, new offerings, joint value, what’s going on?
Stewart: So, Splunk and Pure have had a long relationship around accelerating customer’s analytics, the speed at which they can get their questions answered, the rate at which they can ingest data … to be able to ingest more sources, look at more data, get faster time to take action. Splunk has released a new architecture, a significant evolution from the traditional Splunk architecture. [It’s] disaggregated based off caching and an object store construct called SmartStore.
Martin: Tell us more about Splunk’s SmartStore.
Aleti: What SmartStore brings to the table is that it decouples compute and storage. So now you can scale storage independent of compute. We broke the paradigm of compute and storage co-location and added a small twist: We bring compute and storage closer together only on demand. So, that means when we are running a query or we know we are running a search, and whenever the data is being looked for, that is only when we bring the data together.
The other key thing that we do is we have an active data set. We ensure that SmartStore has a very powerful cache manager that ensures that the active data set is always in the cache — very similar to the RAM on your laptop. The RAM on your laptop has active data sets always in the cache, always on memory. So [that’s] very similar to that SmartStore cache, [which] allows you to have your active data set always locally on the indexer so that your search performance is not impacted.
The SmartStore feature is already available on-premises. We are also already using it to host all of our Splunk cloud deployments as well, and it’s available for customers who want to deploy Splunk on AWS.
Vellante: How does Pure Storage fit with SmartStore?
Stewart: Where we come in relative to SmartStore is we were a co-developer, a launch partner. And because our object offering FlashBlade is a high-performance object store, we are a little bit different than the rest of the Splunk S3 partner ecosystem who have invested in slow, more of an archive-mode of S3. We have always been designed, and betting on the future would be based on high-performance large-scale object [storage]. And so we believe SmartStore is a perfect example of a modern analytics platform.
We’ve done comparison tests with other SmartStore search results that have been published in other vendors’ white papers, and we show FlashBlade, when we run the same benchmark, is 80 times faster.
So, what you can now have with that architecture is confidence. Should you find yourself in a compliance or regulatory issue, something like [General Data Protection Regulation], where you’ve got 72 hours to notify everyone who’s been impacted by a breach [or] any time where you’ve got to go back into history, we’re going to deliver those results faster than any other object store in the market today.
Martin: Does Splunk consider what FlashBlade is doing here an accelerant of Splunk workloads in customer environments?
...
(* Disclosure: TheCUBE is a paid media partner for the Pure//Accelerate event. Neither Pure Storage Inc., the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)
