Skip to content

BuildNot yet confirmed elsewhere1 publisher2 min readPublished

Valkey's Madelyn Olson says async I/O threading lifted one process to about 1M requests a second

Valkey's async I/O threads lifted throughput per process from about 200,000-250,000 to about one million requests a second, AWS's Madelyn Olson told InfoQ. The replication and slot-migration fixes in the same release line make the firmer case for taking the Redis fork seriously.

The Engineer · Build desk

How we use AISend a correction

Illustration accompanying Valkey's Madelyn Olson says async I/O threading lifted one process to about 1M requests a second
Generated illustration

What happened

  • Valkey has twelve maintainers and nine technical steering committee members spread across eight companies, among them Ericsson, AWS, Apple and Percona.
  • Memory-efficiency work in versions 8.0 and 8.1 targeted key embedding and the per-slot dictionary.
  • Version 9 brought numbered databases, the namespaces of single-instance deployments, to cluster mode, removing one reason some users could not move to it.
  • Hash-field expiration, one of the project's most requested features according to the interview, also arrived in version 9.
  • Glide, a client library that began at AWS, puts connection and topology handling in a shared Rust core exposed through per-language bindings.

Compiled by The EngineerSomething wrong?How this is made

Why it matters

  • cost The throughput gain comes from threads, so a process needs spare cores to collect it. Instance sizing built around one busy core per process has to be revisited before the figure means anything.
  • constraint Numbered databases remove one blocker to cluster mode, but cross-slot operations still need their data on one shard. Applications built on multi-key operations still need key design work before they migrate.
  • exposure The maintainers cite Mastodon-style shared clusters as demand for the version 9 changes but warn the arrangement is not strong multi-tenancy. Isolation between tenants stays with the operator.
  • decision Choosing Glide puts one Rust core under every language binding, so a core fix reaches all of them at once and so would a core bug. Native clients, including Go ones, remain supported.

Taken at face value, Olson's figures put the gain at four to five times per process [18]. The interview does not describe the hardware, value sizes, client count or pipelining behind either number [1]. Those variables decide whether a throughput result moves from one team's test setup to another team's cluster. I'd treat the million as a hypothesis to reproduce on production-shaped traffic before it changes a capacity plan.

The control that ships with it is easier to credit. "Unlike the previous I/O-thread arrangement, thread configuration can be changed at runtime, allowing operators to add cores to help handle burst workloads," Olson said [9]. Under the old arrangement the setting could not be changed while the server ran [9]. A setting that moves live can be used during the burst itself.

I think the stronger engineering case is in the replication and cluster work. Before dual-channel replication, a primary syncing a replica sent the full copy of the dataset first and the stream of later changes after it [11]. The 8.x releases send the two in parallel. According to the interview, that reduces memory pressure on the primary during synchronisation [11]. Presumably the saving comes from no longer holding the changes made during the copy on the primary until the copy completes.

Atomic slot migration in version 9 closes a failure mode in resharding. With the old key-by-key method, a failed operation could stop a cluster with only part of its data moved [12]. The new method stages the data in advance and then cuts over, so a migration either completes in full or does not happen at all [12]. I suspect most operators assumed they already had that behaviour.

The project is more than two years past the fork from Redis [7]. Both developers InfoQ interviewed work at companies among the eight that supply its maintainers [8]. Olson works at AWS, sits on the technical steering committee and was a Redis committer before the split [16]. "I helped create the fork after the license change," she said [16]. Viktor Soderqvist works on open source at Ericsson and was also involved in creating the fork [17].

What to watch

  • Synchronous replication: the maintainers propose it to give durability guarantees for data that is not ephemeral, and shipping it would take Valkey past caching.
  • The tiering design, which would keep hot data in DRAM, move colder data to SSD, and possibly use a general interface that could reach S3 or Postgres.
  • An independent reproduction of the one-million-requests figure that publishes hardware, value sizes and client counts.

Clarity's read

What the record supports and how the coverage leans. The claims behind it follow.

Reality

Evidence45
Adoption
Insufficient
Hype gap+20
Incentives65
Confidence50
Why these scores

Claim ledger

Ranked by verification strength, evidence, and original report placement.

  1. [1]

    "Async I/O threading increased throughput from approximately 200,000-250,000 requests per second to around one million per process."

    ReportedSupportedSource: Madelyn Olson, Valkey TSC member at AWS, interviewed by InfoQ2 sources— create a free account to open themView cited source
  2. [2]

    Cluster mode distributes keys by slot across nodes, and cross-slot operations require the data to reside on the same shard.

    ReportedSupportedSource: Madelyn Olson, interviewed by InfoQ2 sources— create a free account to open themView cited source
  3. [3]

    Version 9 added numbered databases, the namespaces available in single-instance deployments, to cluster mode, removing one reason some users could not migrate to cluster mode.

    ReportedSupportedSource: Madelyn Olson, interviewed by InfoQ2 sources— create a free account to open themView cited source

Sources

1 independent publisher whose own reporting we read for this story.

  1. infoq.com

    1 article · October 9, 2026

    Olson and Söderqvist Discuss Valkey’s Evolution and Future Past Caching Use Cases at OSS EU

Share your take

Let Clarity write the post for you.

Signed-in readers get a short post drafted on this story in the register they choose — narrative, analytical, or a direct position — editable to the last word before it goes anywhere. The share buttons at the top of this story work without an account.

Topics and entities

Follow any of these and your For You feed starts watching them — no settings page required.

Topics

Entities

Loading related stories