6 ms·

Show HN: Oodle – serverless, fully-managed, drop-in replacement for Prometheus

84 points by kirankgollu 2y ago

Hello HN! My co-founder, Vijay and I are excited to open up Oodle for everyone. We used to be observability geeks at Rubrik. Our metrics bills grew like 20x over 4 years. We tried to control spend by getting better visibility, blocking high cardinality labels like pod_id, cluster_id, and customer_id. But that made debugging issues complicated. App engineers hated blocking metrics, and blocking others' code reviews was not fun for platform engineers either! Migrations (and lock-ins) were very painful, the first migration from Influx to Signalfx took 6+ months and the second migration from Splunk took over a year. Oodle is taking a new approach to building a cost-efficient serverless metrics observability platform. It delivers fast performance at high scale. We leverage custom storage format on S3, tuned for metrics data. Queries are serverless. The hard part is how to achieve fast performance while optimizing for costs (every cpu cycle, storage/memory byte counts!). We've written about the architecture in more detail on our blog: https://blog.oodle.ai/building-a-high-performance-low-cost-metrics-observability-system/ https://blog.oodle.ai/building-a-high-performance-low-cost-m... Try out our playground with 13M+ active time series/hr & 13B+ samples/day: https://play.oodle.ai https://play.oodle.ai Explore all features with live data via Quick Signup: https://us1.oodle.ai/signup https://us1.oodle.ai/signup - Instant exploration (<5min): Run one command to stream synthetic metrics to your account - Easy integration (<15min): Explore with your data from existing Prometheus or OTel setup. We’d love your feedback! cheers

utf_8x 2y ago
Not to be confused with Oodle[1] [1] https://www.radgametools.com/oodle.htm https://www.radgametools.com/oodle.htm
mt42or 2y ago
VictoriaMetrics is still cheaper!
- kirankgollu 2y ago
  Oodle is a fully managed offering. Curious why you think Victoria Metrics Cloud is still cheaper. https://victoriametrics.com/products/cloud/ https://victoriametrics.com/products/cloud/ This translates to about $5.2 per 1k metrics, Oodle is $1 per 1k metrics! Am I missing something?
  - deepsun 2y ago
    Hmm, where do you see $5.2? I see $0.182/h/1M ts = $0.182 per 1k metrics (S.STARTER.A instance) Also Oodle website says to "Contact for pricing beyond 5M". While VictoriaMetrics Cloud only starts at 1M (S.STARTER.A), and "Contact Us" starts at 125M active time series. PS: time series is only one dimension, there's also storage size, retention, query/alerts frequency etc.
    - deepsun 2y ago
      $0.253/h/1M = $0.182 per 1k metrics per month.
      - kirankgollu 2y ago
        As suggested in earlier message, this pricing is only for single node. imo, this needs to be compared to cluster mode - any company with meaningful scale will need reliabilty and needs to run in cluster mode since you’d need your observability systems to be up and running when the rest of your systems are down.
    - kirankgollu 2y ago
      Oodle is a fully managed, supports high availability, so was comparing against the cluster mode of victoria metrics cloud offering. RE: Victoria Metrics Pricing: Pls see https://victoriametrics.com/products/cloud/ https://victoriametrics.com/products/cloud/. The pricing that you are referring doesn't seem public, looks like you've to sign up to see that pricing. $190/month is a single node pricing. For any real use cases, you need HA and victoria metrics enterprise pricing for a cluster starts at $1300/month for 250k metrics. This translates to $5.2 per 1k metrics (5x more expensive than Oodle). For a real scale about ~2.5M or ~5M time series / hour, Oodle is around half the cost of victoria metrics. RE: Pricing dimensions, we've simplified our pricing by indexing on a single dimension. We don't require our customers to choose machine type, RAM, CPU etc. There are other limits but for the most part, they don't matter so much in our pricing. RE: Pricing tiers, anything more than $30-50k/year (>5M time series / hour), companies usually to talk with someone for volume discounts rather than go with online pricing.
PeterZaitsev 2y ago
Pretty cool. I wonder where it would develop - will Oodle release an Open Source version or will ideas be implemented in some new (or existing) Open Source solutions - ClickHouse, VictoriaMetrics etc.
- dengolius 2y ago
  there is no magic https://oodle.ai/product#magic-behind-oodle https://oodle.ai/product#magic-behind-oodle
  - kirankgollu 2y ago
    It'd be nice to post a disclaimer if you are working on a competing offering before you post a comment. (for the benefit of everyone)
    - dengolius 2y ago
      Sorry, I didn't understand your point... What I did wrong here? )
      - kirankgollu 2y ago
        your comment said "no magic" and the links points to "#magic-behind-oodle". May be I misread your comment or you didn't mean that.
kyyol 2y ago
The Oodle team is great! If you're looking for a cheap metrics (prom/otel) store, check it out! Not to mention they offer the best metrics free tier in the entire space... Let me know if you know of a better free tier ;) Unfortunately, Grafana Cloud only offers 10k active series, which is really easy to surpass even in a homelab; meanwhile, Oodle offers 100k.
- bosch_mind 2y ago
  Is this comment legit? New account, no activity…
  - kyyol 2y ago
    Yeah it's legit. Never bothered to create a HN account but caught wind of this post and had to come drop some good words about the team. I use it (for free) and have no skin in the game. Just want to let folks know of a free tier that is literally 10x better than the next best thing!
rnjn 2y ago
very interesting solution. and great idea to have a playground. would love to know some details on the implementation of the architecture you have shared - 1. how do you query across multiple files, do you have a query engine like data fusion doing that heavy lifting, or is this a custom implementation ? 2. how do you manage a WAL with real time query-ability across files ? have you seen any failures (recent entries missing sort of issues) Thanks, once again really interesting design and intuitively looks more economical.
- mvijaykarthik 2y ago
  Thanks for your feedback, and great questions. 1. We create serverless functions to process each file and then combine the results, optimized for columnar file formats. 2. This is one of our core innovations :) We created custom representations of WALs which help us with query performance and ingesting them quickly. 3. Once a WAL is ingested, it is available for query within a few seconds. So far it has been reliable and we have not had issues with missing data.
navjack27 2y ago
I don't know how trademark works or anything like that not a lawyer etc etc but lots of stuff are called oodle. I wish you luck.
- kirankgollu 2y ago
  Thanks for the heads up. we did check on IP/trademarks just to be sure to avoid violations.
  - TiredOfLife 2y ago
    There is this obscure website, google.com I think is it's name.
    - deleted 2y ago
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  - bayarearefugee 2y ago
    Oodle is a registered trademark: https://uspto.report/TM/88478792 https://uspto.report/TM/88478792 RAD is now owned by Epic Games (acquired in 2021) so they have very deep pockets. A lot of people, including myself, were clearly initially confused that there must be some association given you are using this name in a not-entirely-unrelated field. IANAL but I hope you're real sure that you are legally in the clear before you commit too deeply to the name.
    - kirankgollu 2y ago
      Thanks for your inputs, we will followup.
- alias_neo 2y ago
  This is the one that came to mind for me when I saw Oodle: https://www.radgametools.com/oodle.htm https://www.radgametools.com/oodle.htm
alanfranz 2y ago
Some comparison to Thanos would be great!
- verdverm 2y ago
  Yup, fan of the LGTM stack + Alloy
- mvijaykarthik 2y ago
  Great question! Vijay here, I'm one of the co-founders of Oodle. Compared to thanos 1. We use object store (S3) for all queries - even recent time ranges. Object store is not just an archival solution 2. Customized indexing to minimize memory usage. Index is also on object storage. 3. Custom columnar file format optimized for storing metrics on object storage 4. Serverless functions for achieving good query performance. This helps us break down and parallelise queries without impacting cost with pre-provisioned compute. 5. No downsampling. Downsampling is not required to improve query performance or reduce costs with serverless and object storage
nileshbansal 2y ago
We, at Workorb, migrated from Grafana to Oodle and very happy so far. Observability space does need a ground up reimagination and we think Oodle is positioned to do that.
- ijidak 2y ago
  I'm curious, why did you move off of grafana? For the same reasons op listed or for other reasons?
  - nileshbansal 2y ago
    For us, cost, specially as we grow and number of metrics and tags increase was a factor. We are also starting use Oodle AI for helping with discovery of problem root cause faster.
neetip 2y ago
[flagged]
thinkmassive 2y ago
Is it SaaS-only?
- bradfitz 2y ago
  If it weren't, then you'd need servers and it couldn't be serverless! :)
  - kirankgollu 2y ago
    This architecture diagram (https://oodle.ai/product#magicbehindoodle https://oodle.ai/product#magicbehindoodle) goes into more detail into where we leverage Serverless. For ingestion, we still use dedicated compute, but for queries, we leverage serverless.
  - mike_d 2y ago
    "Serverless" is an overloaded term marketing that really means functions-as-a-service. Looking at the stack, I don't actually see any components that you couldn't easily port to an on-prem solution.
- kirankgollu 2y ago
  yes, it's only fully managed at this time. However, oodle is very cost-efficient, it's cheaper than your self-hosted infra costs. https://oodle.ai/usecases/self-hosted https://oodle.ai/usecases/self-hosted
  - someguy101010 2y ago
    any plans to open source? I feel very comfortable using neon.tech (separates compute from storage for postgres) b/c they open source their stack but it would be hard for me to adopt something like oodle without an open source version.
    - kirankgollu 2y ago
      We don’t have plan to open source at this time. Many observability solutions are closed source. Could you please describe why you would require this to be open source vs open source compatible? We think Oodle combines the benefits of open source (compatibility, no lock-in) with the operational simplicity, reliability of commercial vendors. Some products might give a false illusion of no-lock in just because it's open source, it wouldn’t mean you don't have lock-ins. We believe what really matters is "Open Source Compatible" - i.e. how easy it is to get in? How easy is it to switch out? (to a de-facto open source standard like Prometheus/Grafana should you need to disconnect ties with the vendor). Security and compliance is the other big part - we are working on adding compliance like SOC2, CCPA etc.
suntracks 2y ago
Love the observability feature here. Would love to see a detailed feature set comparision along on the competetitors landscape
- kirankgollu 2y ago
  Thanks for the kind words - we will be posting a feature comparison matrix in the upcoming weeks on our website.
protocolture 2y ago
"fully managed, serverless" So its not really a drop in replacement for prometheus then, its more of a send all your data to some other bloke kind of replacement. Software as a service is fine, but you dont need to hide it behind hip marketing terminology.
- mvijaykarthik 2y ago
  Technically you are correct, the scraper will still exist. However, the hard part is scaling the query and storage layers which we replace.
infecto 2y ago
The logo on your main page for oodle.ai is blurry. Why use a .ai domain? I love LLM but this is a turnoff to me.
- kirankgollu 2y ago
  thanks for the pointer on logo - we are fixing it later today. Edit: fixed now.
- nikau 2y ago
  its steam from the japanese onsen
- mvijaykarthik 2y ago
  We are still early in our journey, and are currently working on leveraging LLMs for incidents and query / dashboard generation. We do use pre-LLM-era AI and statistical analysis to provide insights and auto create dashboards for alerts (currently in alpha).
weego 2y ago
Why is the primary sales call to action is that it's serverless if it's a hosted solution? Who cares.
- memset 2y ago
  Because at the early stages it’s really important to talk to customers. This also helps find users for whom this is a huge pain point - metrics costs are so high that they’d love to talk to someone and complain about the problem.
  - beaker52 2y ago
    “fully-managed, cheap metrics, ideal for serverless applications”
    - kirankgollu 2y ago
      we leverage serverless and s3 based architecture for much lower costs. However, it's applies for any application, not just for serverless applications.
      - beaker52 2y ago
        Your costs and deployment pattern are your problem, customers don’t care about them. Saying it is serverless means nothing to customers unless the serverless aspect applies to them, which in this case it doesn’t. If you’re only selling access to your product for a fee, then whether it’s serverless or not, customers couldn’t care less.
        kirankgollu 2y ago
        That's fair. We actually started with "reduce your costs by 3-10x with infinite scalability" without talking about storing in s3 and serverless (along the lines of your thinking - only talk about benefits + what you do). But our users, engineers by their very nature, were skeptical about how Oodle works, so we ended up settling on a combination of why, what and how. This resonated better with our early customers and prospects.
manishsharan 2y ago
I have been meaning to ask the observability experts this question: Why not dump all metrics , events and logs into Clickhouse ? and purge data as necessary? For small to medium sized businesses/solution ecosystem, will this be be enough ?
- deepsun 2y ago
  Very different tools, applications almost don't intersect actually. ClickHouse is an analytical database (for events). Yes, you can do metrics in there (or PostgreSQL for that matter). Observability has their own needs, so specialized solutions work better, more integrations and out-of-the box tooling already provided. With generic databases it's more like a constructor that you'd need to develop a lot to become workable. For example, let's say you have 50m active time series, with 1%/hour churn rate. What would be the database structure in ClickHouse? (my answer is that I don't know. I know mostly VictoriaMetrics, and there's no such question there, the structure is already implemented).
- iampims 2y ago
  It'll work. Clickhouse has even experimental support for storing prometheus metrics natively. A big missing piece is alerting.
  - kirankgollu 2y ago
    ClickHouse is great for logs and traces, however, for metrics, it is still in the early phase. ClickHouse is also a general purpose, real time analytics database. See clickhouse.com. Whereas Oodle is specifically built for end-to-end metrics observability.
    - rnjn 2y ago
      Curious to know what you mean by "early phase" here.
      - kirankgollu 2y ago
devmor 2y ago
Why did you name your startup the same name as the most popular network compression library for video games? This seems short sighted. Even if you don't run afoul of trademark/copyright, you're sharing a lot of SEO and marketing terminology.
- kirankgollu 2y ago
  Point taken. Thanks for the feedback. Our reasoning is that we’d like the name to be short and memorable. And a bunch of observability companies have observe keyword overloaded all over the place, we wanted our name to stand out. Oodle = Optimized Observability Data Lake.
shivarevanth 2y ago
[flagged]
- kirankgollu 2y ago
  With our custom columnar format and indexes, we are able to filter relevant data files where high cardinality column is present. This helps us to keep the queries faster for high cardinality labels as well, thus, allowing us to quickly drill down on specific pod_id/cluster_id/customer_id kind of labels.
deleted 2y ago
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- deleted 2y ago
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estebarb 2y ago
I'm wondering something: how is the storage/compactation solved? AFAIK S3 lacks append semantics, so data must be accumulated somewhere else before storing it. Kinesis?
- mvijaykarthik 2y ago
  We use a local disk to temporarily stage data before putting it on S3. We have smaller WAL (write ahead log) objects, and a periodic compaction process which creates read-optimized files on S3.
CubsFan1060 2y ago
The UI feels _very_ similar to Grafana. Even the dashboard folders look exactly the same to me. I would have thought that Grafana being AGPL woudl specifically forbid this? Edit: Or maybe the AGPL just requires releasing any code you change? I could be confused.
- kirankgollu 2y ago
  It’s indeed Grafana. We’ve been maintaing a public fork of Grafana.
  - CubsFan1060 2y ago
    Where do you keep the code? Found it: https://github.com/oodle-ai/grafana https://github.com/oodle-ai/grafana Why do this instead of just build a data source? Edit: Not to be that guy (but I'm about to be that guy). You have links to grafana.com (which, is your competitor), all over the source in your page. This also lists the version as 11.1.0, which was released 6-21. All of the versions in your fork repo mention 11.0.0-pre. Did I find the wrong repo, or are you using code that you haven't published? The reason I mostly care is that this is the sort of reason that good open source projects get closed down, and that makes me a bit sad.
    - mvijaykarthik 2y ago
      Oodle can be utilized solely as a datasource, but we also wanted to provide a solution for customers who don’t have a visualization platform in place. Here is the branch we use: https://github.com/oodle-ai/grafana/tree/v11.1.0-oodle-stable https://github.com/oodle-ai/grafana/tree/v11.1.0-oodle-stabl..., which has all the changes we have made in Grafana.
      - sosodev 2y ago
        So the vast majority of your fork is just rebranding? Customers get to lose thousands of commits worth of improvements for that?
TripleChecker 2y ago
Cool! The website says “No Lock-In” does it mean that I can bring by own compute and storage? Also, found a few typos and a broken link, see error report here: https://triplechecker.com/s/xEd4Hp/oodle.ai?v=uxGS1 https://triplechecker.com/s/xEd4Hp/oodle.ai?v=uxGS1
- kirankgollu 2y ago
  Thanks for the report - we just deployed fix for the same. No lock-in means it’s 100% open source (PromQL) compatible. You can swap out vendors or move to self-hosted open source solutions should you need to move away from Oodle. When you migrate out, you get to export all your data, dashboards and alerts. you don't need to make any code changes. We support bringing your own bucket (BYOB) for large enterprise customers however, you cannot bring your own compute at this time. Our thoughts are along the lines of how Snowflake approached the problem - everything fully managed to keep the operational overhead minimal. https://jack-vanlightly.com/blog/2023/9/25/on-the-future-of-cloud-services-and-byoc https://jack-vanlightly.com/blog/2023/9/25/on-the-future-of-...
sidd22 2y ago
[flagged]
- kirankgollu 2y ago
  Our P99 query latency is under 3 seconds, we have tested up to 100M unique time series / hour and the architecture can scale up to billion time series / hour. To get a feel of the performance at high scale, give us a try at https://play.oodle.ai https://play.oodle.ai

84 points by kirankgollu 2y ago

utf_8x 2y ago

Not to be confused with Oodle[1] [1] https://www.radgametools.com/oodle.htm https://www.radgametools.com/oodle.htm

mt42or 2y ago

VictoriaMetrics is still cheaper!

kirankgollu 2y ago
Oodle is a fully managed offering. Curious why you think Victoria Metrics Cloud is still cheaper. https://victoriametrics.com/products/cloud/ https://victoriametrics.com/products/cloud/ This translates to about $5.2 per 1k metrics, Oodle is $1 per 1k metrics! Am I missing something?
- deepsun 2y ago
  Hmm, where do you see $5.2? I see $0.182/h/1M ts = $0.182 per 1k metrics (S.STARTER.A instance) Also Oodle website says to "Contact for pricing beyond 5M". While VictoriaMetrics Cloud only starts at 1M (S.STARTER.A), and "Contact Us" starts at 125M active time series. PS: time series is only one dimension, there's also storage size, retention, query/alerts frequency etc.
  - deepsun 2y ago
    $0.253/h/1M = $0.182 per 1k metrics per month.
    - kirankgollu 2y ago
      As suggested in earlier message, this pricing is only for single node. imo, this needs to be compared to cluster mode - any company with meaningful scale will need reliabilty and needs to run in cluster mode since you’d need your observability systems to be up and running when the rest of your systems are down.
  - kirankgollu 2y ago
    Oodle is a fully managed, supports high availability, so was comparing against the cluster mode of victoria metrics cloud offering. RE: Victoria Metrics Pricing: Pls see https://victoriametrics.com/products/cloud/ https://victoriametrics.com/products/cloud/. The pricing that you are referring doesn't seem public, looks like you've to sign up to see that pricing. $190/month is a single node pricing. For any real use cases, you need HA and victoria metrics enterprise pricing for a cluster starts at $1300/month for 250k metrics. This translates to $5.2 per 1k metrics (5x more expensive than Oodle). For a real scale about ~2.5M or ~5M time series / hour, Oodle is around half the cost of victoria metrics. RE: Pricing dimensions, we've simplified our pricing by indexing on a single dimension. We don't require our customers to choose machine type, RAM, CPU etc. There are other limits but for the most part, they don't matter so much in our pricing. RE: Pricing tiers, anything more than $30-50k/year (>5M time series / hour), companies usually to talk with someone for volume discounts rather than go with online pricing.

PeterZaitsev 2y ago

Pretty cool. I wonder where it would develop - will Oodle release an Open Source version or will ideas be implemented in some new (or existing) Open Source solutions - ClickHouse, VictoriaMetrics etc.

dengolius 2y ago
there is no magic https://oodle.ai/product#magic-behind-oodle https://oodle.ai/product#magic-behind-oodle
- kirankgollu 2y ago
  It'd be nice to post a disclaimer if you are working on a competing offering before you post a comment. (for the benefit of everyone)
  - dengolius 2y ago
    Sorry, I didn't understand your point... What I did wrong here? )
    - kirankgollu 2y ago
      your comment said "no magic" and the links points to "#magic-behind-oodle". May be I misread your comment or you didn't mean that.

kyyol 2y ago

The Oodle team is great! If you're looking for a cheap metrics (prom/otel) store, check it out! Not to mention they offer the best metrics free tier in the entire space... Let me know if you know of a better free tier ;) Unfortunately, Grafana Cloud only offers 10k active series, which is really easy to surpass even in a homelab; meanwhile, Oodle offers 100k.

bosch_mind 2y ago
Is this comment legit? New account, no activity…
- kyyol 2y ago
  Yeah it's legit. Never bothered to create a HN account but caught wind of this post and had to come drop some good words about the team. I use it (for free) and have no skin in the game. Just want to let folks know of a free tier that is literally 10x better than the next best thing!

rnjn 2y ago

very interesting solution. and great idea to have a playground. would love to know some details on the implementation of the architecture you have shared - 1. how do you query across multiple files, do you have a query engine like data fusion doing that heavy lifting, or is this a custom implementation ? 2. how do you manage a WAL with real time query-ability across files ? have you seen any failures (recent entries missing sort of issues) Thanks, once again really interesting design and intuitively looks more economical.

mvijaykarthik 2y ago
Thanks for your feedback, and great questions. 1. We create serverless functions to process each file and then combine the results, optimized for columnar file formats. 2. This is one of our core innovations :) We created custom representations of WALs which help us with query performance and ingesting them quickly. 3. Once a WAL is ingested, it is available for query within a few seconds. So far it has been reliable and we have not had issues with missing data.

navjack27 2y ago

I don't know how trademark works or anything like that not a lawyer etc etc but lots of stuff are called oodle. I wish you luck.

kirankgollu 2y ago
Thanks for the heads up. we did check on IP/trademarks just to be sure to avoid violations.
- TiredOfLife 2y ago
  There is this obscure website, google.com I think is it's name.
  - deleted 2y ago
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- bayarearefugee 2y ago
  Oodle is a registered trademark: https://uspto.report/TM/88478792 https://uspto.report/TM/88478792 RAD is now owned by Epic Games (acquired in 2021) so they have very deep pockets. A lot of people, including myself, were clearly initially confused that there must be some association given you are using this name in a not-entirely-unrelated field. IANAL but I hope you're real sure that you are legally in the clear before you commit too deeply to the name.
  - kirankgollu 2y ago
    Thanks for your inputs, we will followup.
alias_neo 2y ago
This is the one that came to mind for me when I saw Oodle: https://www.radgametools.com/oodle.htm https://www.radgametools.com/oodle.htm

alanfranz 2y ago

Some comparison to Thanos would be great!

verdverm 2y ago
Yup, fan of the LGTM stack + Alloy
mvijaykarthik 2y ago
Great question! Vijay here, I'm one of the co-founders of Oodle. Compared to thanos 1. We use object store (S3) for all queries - even recent time ranges. Object store is not just an archival solution 2. Customized indexing to minimize memory usage. Index is also on object storage. 3. Custom columnar file format optimized for storing metrics on object storage 4. Serverless functions for achieving good query performance. This helps us break down and parallelise queries without impacting cost with pre-provisioned compute. 5. No downsampling. Downsampling is not required to improve query performance or reduce costs with serverless and object storage

nileshbansal 2y ago

We, at Workorb, migrated from Grafana to Oodle and very happy so far. Observability space does need a ground up reimagination and we think Oodle is positioned to do that.

ijidak 2y ago
I'm curious, why did you move off of grafana? For the same reasons op listed or for other reasons?
- nileshbansal 2y ago
  For us, cost, specially as we grow and number of metrics and tags increase was a factor. We are also starting use Oodle AI for helping with discovery of problem root cause faster.

neetip 2y ago

[flagged]

thinkmassive 2y ago

Is it SaaS-only?

bradfitz 2y ago
If it weren't, then you'd need servers and it couldn't be serverless! :)
- kirankgollu 2y ago
  This architecture diagram (https://oodle.ai/product#magicbehindoodle https://oodle.ai/product#magicbehindoodle) goes into more detail into where we leverage Serverless. For ingestion, we still use dedicated compute, but for queries, we leverage serverless.
- mike_d 2y ago
  "Serverless" is an overloaded term marketing that really means functions-as-a-service. Looking at the stack, I don't actually see any components that you couldn't easily port to an on-prem solution.
kirankgollu 2y ago
yes, it's only fully managed at this time. However, oodle is very cost-efficient, it's cheaper than your self-hosted infra costs. https://oodle.ai/usecases/self-hosted https://oodle.ai/usecases/self-hosted
- someguy101010 2y ago
  any plans to open source? I feel very comfortable using neon.tech (separates compute from storage for postgres) b/c they open source their stack but it would be hard for me to adopt something like oodle without an open source version.
  - kirankgollu 2y ago
    We don’t have plan to open source at this time. Many observability solutions are closed source. Could you please describe why you would require this to be open source vs open source compatible? We think Oodle combines the benefits of open source (compatibility, no lock-in) with the operational simplicity, reliability of commercial vendors. Some products might give a false illusion of no-lock in just because it's open source, it wouldn’t mean you don't have lock-ins. We believe what really matters is "Open Source Compatible" - i.e. how easy it is to get in? How easy is it to switch out? (to a de-facto open source standard like Prometheus/Grafana should you need to disconnect ties with the vendor). Security and compliance is the other big part - we are working on adding compliance like SOC2, CCPA etc.

suntracks 2y ago

Love the observability feature here. Would love to see a detailed feature set comparision along on the competetitors landscape

kirankgollu 2y ago
Thanks for the kind words - we will be posting a feature comparison matrix in the upcoming weeks on our website.

protocolture 2y ago

"fully managed, serverless" So its not really a drop in replacement for prometheus then, its more of a send all your data to some other bloke kind of replacement. Software as a service is fine, but you dont need to hide it behind hip marketing terminology.

mvijaykarthik 2y ago
Technically you are correct, the scraper will still exist. However, the hard part is scaling the query and storage layers which we replace.

infecto 2y ago

The logo on your main page for oodle.ai is blurry. Why use a .ai domain? I love LLM but this is a turnoff to me.

kirankgollu 2y ago
thanks for the pointer on logo - we are fixing it later today. Edit: fixed now.
nikau 2y ago
its steam from the japanese onsen
mvijaykarthik 2y ago
We are still early in our journey, and are currently working on leveraging LLMs for incidents and query / dashboard generation. We do use pre-LLM-era AI and statistical analysis to provide insights and auto create dashboards for alerts (currently in alpha).

weego 2y ago

Why is the primary sales call to action is that it's serverless if it's a hosted solution? Who cares.

memset 2y ago
Because at the early stages it’s really important to talk to customers. This also helps find users for whom this is a huge pain point - metrics costs are so high that they’d love to talk to someone and complain about the problem.
- beaker52 2y ago
  “fully-managed, cheap metrics, ideal for serverless applications”
  - kirankgollu 2y ago
    we leverage serverless and s3 based architecture for much lower costs. However, it's applies for any application, not just for serverless applications.
    - beaker52 2y ago
      Your costs and deployment pattern are your problem, customers don’t care about them. Saying it is serverless means nothing to customers unless the serverless aspect applies to them, which in this case it doesn’t. If you’re only selling access to your product for a fee, then whether it’s serverless or not, customers couldn’t care less.
      - kirankgollu 2y ago
        That's fair. We actually started with "reduce your costs by 3-10x with infinite scalability" without talking about storing in s3 and serverless (along the lines of your thinking - only talk about benefits + what you do). But our users, engineers by their very nature, were skeptical about how Oodle works, so we ended up settling on a combination of why, what and how. This resonated better with our early customers and prospects.

manishsharan 2y ago

I have been meaning to ask the observability experts this question: Why not dump all metrics , events and logs into Clickhouse ? and purge data as necessary? For small to medium sized businesses/solution ecosystem, will this be be enough ?

deepsun 2y ago
Very different tools, applications almost don't intersect actually. ClickHouse is an analytical database (for events). Yes, you can do metrics in there (or PostgreSQL for that matter). Observability has their own needs, so specialized solutions work better, more integrations and out-of-the box tooling already provided. With generic databases it's more like a constructor that you'd need to develop a lot to become workable. For example, let's say you have 50m active time series, with 1%/hour churn rate. What would be the database structure in ClickHouse? (my answer is that I don't know. I know mostly VictoriaMetrics, and there's no such question there, the structure is already implemented).
iampims 2y ago
It'll work. Clickhouse has even experimental support for storing prometheus metrics natively. A big missing piece is alerting.
- kirankgollu 2y ago
  ClickHouse is great for logs and traces, however, for metrics, it is still in the early phase. ClickHouse is also a general purpose, real time analytics database. See clickhouse.com. Whereas Oodle is specifically built for end-to-end metrics observability.
  - rnjn 2y ago
    Curious to know what you mean by "early phase" here.
    - kirankgollu 2y ago

devmor 2y ago

Why did you name your startup the same name as the most popular network compression library for video games? This seems short sighted. Even if you don't run afoul of trademark/copyright, you're sharing a lot of SEO and marketing terminology.

kirankgollu 2y ago
Point taken. Thanks for the feedback. Our reasoning is that we’d like the name to be short and memorable. And a bunch of observability companies have observe keyword overloaded all over the place, we wanted our name to stand out. Oodle = Optimized Observability Data Lake.

shivarevanth 2y ago

[flagged]

kirankgollu 2y ago
With our custom columnar format and indexes, we are able to filter relevant data files where high cardinality column is present. This helps us to keep the queries faster for high cardinality labels as well, thus, allowing us to quickly drill down on specific pod_id/cluster_id/customer_id kind of labels.

deleted 2y ago

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estebarb 2y ago

I'm wondering something: how is the storage/compactation solved? AFAIK S3 lacks append semantics, so data must be accumulated somewhere else before storing it. Kinesis?

mvijaykarthik 2y ago
We use a local disk to temporarily stage data before putting it on S3. We have smaller WAL (write ahead log) objects, and a periodic compaction process which creates read-optimized files on S3.

CubsFan1060 2y ago

The UI feels _very_ similar to Grafana. Even the dashboard folders look exactly the same to me. I would have thought that Grafana being AGPL woudl specifically forbid this? Edit: Or maybe the AGPL just requires releasing any code you change? I could be confused.

kirankgollu 2y ago
It’s indeed Grafana. We’ve been maintaing a public fork of Grafana.
- CubsFan1060 2y ago
  Where do you keep the code? Found it: https://github.com/oodle-ai/grafana https://github.com/oodle-ai/grafana Why do this instead of just build a data source? Edit: Not to be that guy (but I'm about to be that guy). You have links to grafana.com (which, is your competitor), all over the source in your page. This also lists the version as 11.1.0, which was released 6-21. All of the versions in your fork repo mention 11.0.0-pre. Did I find the wrong repo, or are you using code that you haven't published? The reason I mostly care is that this is the sort of reason that good open source projects get closed down, and that makes me a bit sad.
  - mvijaykarthik 2y ago
    Oodle can be utilized solely as a datasource, but we also wanted to provide a solution for customers who don’t have a visualization platform in place. Here is the branch we use: https://github.com/oodle-ai/grafana/tree/v11.1.0-oodle-stable https://github.com/oodle-ai/grafana/tree/v11.1.0-oodle-stabl..., which has all the changes we have made in Grafana.
    - sosodev 2y ago
      So the vast majority of your fork is just rebranding? Customers get to lose thousands of commits worth of improvements for that?

TripleChecker 2y ago

Cool! The website says “No Lock-In” does it mean that I can bring by own compute and storage? Also, found a few typos and a broken link, see error report here: https://triplechecker.com/s/xEd4Hp/oodle.ai?v=uxGS1 https://triplechecker.com/s/xEd4Hp/oodle.ai?v=uxGS1

kirankgollu 2y ago
Thanks for the report - we just deployed fix for the same. No lock-in means it’s 100% open source (PromQL) compatible. You can swap out vendors or move to self-hosted open source solutions should you need to move away from Oodle. When you migrate out, you get to export all your data, dashboards and alerts. you don't need to make any code changes. We support bringing your own bucket (BYOB) for large enterprise customers however, you cannot bring your own compute at this time. Our thoughts are along the lines of how Snowflake approached the problem - everything fully managed to keep the operational overhead minimal. https://jack-vanlightly.com/blog/2023/9/25/on-the-future-of-cloud-services-and-byoc https://jack-vanlightly.com/blog/2023/9/25/on-the-future-of-...

sidd22 2y ago

[flagged]

kirankgollu 2y ago
Our P99 query latency is under 3 seconds, we have tested up to 100M unique time series / hour and the architecture can scale up to billion time series / hour. To get a feel of the performance at high scale, give us a try at https://play.oodle.ai https://play.oodle.ai