A Kafka-compatible data streaming platform built on top of object storage: no inter-zone costs, no disks to manage, and infinitely scalable within your VPC.
In our latest blog post, we describe how WarpStreamโs multi-region infrastructure presents as a single pane of glass in the web console while still being resilient to regional failures.
Introducing WarpStream Managed Data Pipelines. Like managed connectors, but in your VPC. Embeds the Benthos you know and love, but with WarpStream's signature data plane / control plane split.
WarpStream's BYOC control plane and Serverless clusters are now available in multiple new regions!
You can now configure your WarpStream BYOC cluster to use us-east-1, us-west-2, eu-central-1, or ap-southeast-1 in AWS.
We also added ap-southeast-1 for Serverless clusters.
With MSK, it's easy to get started, but hard to scale. Read about how Pixel Federation migrated to WarpStream to flex their clusters across multiple cloud accounts and reduce their Kafka spend by 83%!
Check out our latest blog post to learn about how the
@awscloud
S3 Express One Zone storage class can reduce WarpStream latency by 4x, while still keeping costs and operations burden under control!
We're very excited to have this one featured on the AWS
In addition to
@warpstream_labs
being SOC 2 Type I certified, we are now SOC 2 Type II certified. This reinforces our best-in-class security practices and production readiness. Learn more and request our report via our Trust Center ๐ .
Happy Friday! We just released support for Apache Kafka's idempotent producer functionality. Just upgrade to Agent version >= 515 and start producing ๐
Wouldn't it be great if you could run Kafka in your own environment, eliminate inter-zone networking fees, never have data leave your environment and not have to worry about cross-account permissions? You can with
@warpstream_labs
Bring Your Own Cloud.
Learn why cloud disks are so expensive for Kafka (hint: replication plays a big part) and how moving to object storage (used by
@warpstream_labs
) can reduce costs ๐
Interested in learning more about
@warpstream_labs
zero disk architecture and how it makes Kafka cheaper and simpler? Check out
@richardartoul
's complete Kafka Summit London talk.
WarpStream's BYOC deployment model is different from the BYOC models that you might be familiar with. Check out our latest blog post to learn what makes WarpStream BYOC secure by default.
The phases of cloud infrastructure:
1๏ธโฃ Software given away. Add-ons sold.
2๏ธโฃ Cloud migration. Costs went up instead of down.
3๏ธโฃ Lift and shift BYOC with lots of fees.
Learn how
@warpstream_labs
was developed as cloud first to solve these issues ๐
What if you could handle workloads that spike 10x, as well as a 4x growth in traffic, all while massively reducing your Kafka costs and eliminating manual operations? Learn how
@Middleware_Labs
, an observability company, did that with
@warpstream_labs
.
I would love a logging solution that didn't cost an arm and a leg and allowed me to store logs indefinitely. Using WarpStream, Flink and Iceberg might be the combination to do it. I wrote a post on combining these tools for cost effective logging
Kafka does not need to be complex to manage or costly to operate. Co-founder
@ryanworl
goes over how
@warpstream_labs
architecture makes this possible in this
@DataCouncilAI
presentation.
.
@warpstream_labs
Zero Disk Architecture offers a benefits like:
๐ Auto-scaling based w/no custom tooling.
๐ช Workload isolation via Agent groups.
๐ค Easy data integration via Managed Data Pipelines.
๐ Zero-access BYOC deployment.
Learn more ๐
Join
@warpstream_labs
@caleb_grillo
on July 18 at 6:30 PT as he presents to Big Data Bellevue about how
@warpstream_labs
stateless architecture backed by object storage lowers Kafka costs + operational overhead. Hybrid event; attend in person or online.
๐ธ It's a bold claim we're making: that we can reduce Kafka costs by as much as 10x (by removing inter-AZ networking fees and using object storage). See how our benchmarks show how we do that. ๐
๐ฆ Check out how you can use Kwack to easily read Kafka topics from
@warpstream_labs
and then persist that data to
@duckdb
, as well as export to Parquet ๐
How fast can you put together real-time security monitoring ?
@RisingWaveLabs
shows you how using:
โ๏ธ
@warpstream_labs
as the Kafka-compatible streaming backbone for logs.
๐ข๏ธ
@RisingWaveLabs
as the streaming database.
๐
@grafana
as the dashboard.
Learn how you can use Bento, an open source stream processing framework, to send
@warpstream_labs
topic data to
@paradedb
, a search- and analytics-optimized version of Postgres ๐
Tiered storage for Kafka is a classic tarpit idea. It makes all the sense in the world, but it doesn't work in practice. Check out our latest blog post to learn why.
Tiered storage for Kafka does not actually address these two issues:
๐คฌ Complexity and operational burden.
๐ฐ Costs (specifically, inter-zone networking fees).
In fact, it makes them worse. Learn why ๐
Thanks to
@timeplusdata
for having us on "Streaming Caffeine" to discuss WarpStream at
#Current23
. We covered the history of WarpStream, how WarpStream reduces both costs AND ops pain, and our future "serverless" tier to spin up a cluster in milliseconds.
.
@pixelfederation
's mobile games have millions of users, so you can imagine how many events and topics they have. By swapping MSK for
@warpstream_labs
, they reduced their costs and ditched complex VPC peering in favor of simpler agent groups โก๏ธ
Python stream processing (via
@Quix_io
) and
@warpstream_labs
? Yes, please. See how simple it is to build this pipeline:
Activity logs (Quix) โก๏ธ Topic (WarpStream) โก๏ธ Aggregate results (Quix) โก๏ธ Topic (WarpStream) โก๏ธ Write data to
@duckdb
โก๏ธ Query the data
See how easy it is to create topics in
@warpstream_labs
and stream the data to
@ArroyoSystems
for querying and data pipelines. Go here for our full integration guide ๐
Cloud-native architecture brings benefits to streaming platforms.
@sap1ens
shares an overview and notes that "after 7+ years of running and interacting with all these platforms, I can genuinely say thatย
@warpstream_labs
is the easiest platform to run." โก๏ธ
.
@warpstream_labs
stateless architecture drastically lowers Kafka costs and keeps operations simple. As noted in this
@AWS_Storage
blog, for those that need 4x lower end-to-end latency (from producer to consumer), you can leverage S3 Express One Zone ๐
If you're dealing with A LOT of Kafka data like
@agoda
, you may run into issues with load balancing and over-provisioning. When you move from a stateful to stateless architecture like
@warpstream_labs
, you don't have to worry about over-provisioning ๐
Measuring consumer group lag using offsets isn't always the best approach. Time lag makes it much easier to monitor and troubleshoot consumer groups. Time lag measurement is built directly into
@warpstream_labs
โ no third-party tooling is needed ๐
File this under "it just works." You can connect a
@warpstream_labs
topic to
@timeplusdata
, a stream processing platform, is less than a minute. Then you can visualize the data, run queries, create a materialized view and more. Learn more โก๏ธ