How can I keep Google Cloud Functions warm?
I know this misses the point of using Cloud Functions in the first place, but in my specific case, I'm using Cloud Functions because it's the only way I can bridge Next.js with Firebase Hosting. I don't need to make it cost-efficient, etc.
With that said, the cold boot times for Cloud Functions are simply unbearable and not production-ready, averaging around 10 to 15 SECONDS (WTF?) for my boilerplate.
I've certainly watched this video by Google (https://www.youtube.com/watch?v=IOXrwFqR6kY) that talks about how to reduce cold boot time. In a nutshell: 1) Trim dependencies, 2) Trial & error for dependencies' versions for cache on Google's network, 3) Lazy loading.
But hey, 1) there are only so many dependencies I can trim. 2) What a really useless advice! How would I know which version is more cached? 3) There are only so many dependencies I can lazy load.
Another way is to avoid the cold boot all together. What's a good way or hack that I can essentially keep my (one and only) cloud function warm?
google-cloud-functions firebase-hosting serverless next.js
add a comment |
I know this misses the point of using Cloud Functions in the first place, but in my specific case, I'm using Cloud Functions because it's the only way I can bridge Next.js with Firebase Hosting. I don't need to make it cost-efficient, etc.
With that said, the cold boot times for Cloud Functions are simply unbearable and not production-ready, averaging around 10 to 15 SECONDS (WTF?) for my boilerplate.
I've certainly watched this video by Google (https://www.youtube.com/watch?v=IOXrwFqR6kY) that talks about how to reduce cold boot time. In a nutshell: 1) Trim dependencies, 2) Trial & error for dependencies' versions for cache on Google's network, 3) Lazy loading.
But hey, 1) there are only so many dependencies I can trim. 2) What a really useless advice! How would I know which version is more cached? 3) There are only so many dependencies I can lazy load.
Another way is to avoid the cold boot all together. What's a good way or hack that I can essentially keep my (one and only) cloud function warm?
google-cloud-functions firebase-hosting serverless next.js
add a comment |
I know this misses the point of using Cloud Functions in the first place, but in my specific case, I'm using Cloud Functions because it's the only way I can bridge Next.js with Firebase Hosting. I don't need to make it cost-efficient, etc.
With that said, the cold boot times for Cloud Functions are simply unbearable and not production-ready, averaging around 10 to 15 SECONDS (WTF?) for my boilerplate.
I've certainly watched this video by Google (https://www.youtube.com/watch?v=IOXrwFqR6kY) that talks about how to reduce cold boot time. In a nutshell: 1) Trim dependencies, 2) Trial & error for dependencies' versions for cache on Google's network, 3) Lazy loading.
But hey, 1) there are only so many dependencies I can trim. 2) What a really useless advice! How would I know which version is more cached? 3) There are only so many dependencies I can lazy load.
Another way is to avoid the cold boot all together. What's a good way or hack that I can essentially keep my (one and only) cloud function warm?
google-cloud-functions firebase-hosting serverless next.js
I know this misses the point of using Cloud Functions in the first place, but in my specific case, I'm using Cloud Functions because it's the only way I can bridge Next.js with Firebase Hosting. I don't need to make it cost-efficient, etc.
With that said, the cold boot times for Cloud Functions are simply unbearable and not production-ready, averaging around 10 to 15 SECONDS (WTF?) for my boilerplate.
I've certainly watched this video by Google (https://www.youtube.com/watch?v=IOXrwFqR6kY) that talks about how to reduce cold boot time. In a nutshell: 1) Trim dependencies, 2) Trial & error for dependencies' versions for cache on Google's network, 3) Lazy loading.
But hey, 1) there are only so many dependencies I can trim. 2) What a really useless advice! How would I know which version is more cached? 3) There are only so many dependencies I can lazy load.
Another way is to avoid the cold boot all together. What's a good way or hack that I can essentially keep my (one and only) cloud function warm?
google-cloud-functions firebase-hosting serverless next.js
google-cloud-functions firebase-hosting serverless next.js
edited Aug 10 '18 at 9:08
asked Aug 10 '18 at 9:00
harrisonlo
2118
2118
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2 Answers
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With all "serverless" compute providers, there is always going to be some form of cold start cost that you can't eliminate. Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost. Then, when load decreases, the unnecessary instances will be shut down.
There are ways to minimize your cold start costs, as you have discovered, but the costs can't be eliminated.
If you absolutely demand hot servers to handle requests 24/7, then you need to manage your own servers that run 24/7 (and pay the cost of those servers running 24/7). As you can see, the benefit of serverless is that you don't manage or scale your own servers, and you only pay for what you use, but you have unpredictable cold start costs associated with your project. That's the tradeoff.
add a comment |
You're not the first to ask ;-)
The answer is to configure a remote service to periodically call your function so that the single|only instance remains alive.
It's unclear from your question but I assume your Function provides an HTTP endpoint. In that case, find a healthcheck or cron service that can be configured to make an HTTP call every x seconds|minutes and point it at your Function.
You may have to juggle the timings to find the Goldilocks period -- not too often that that you're wasting effort, not too infrequently that it dies -- but this is what others have done.
Thanks for answering! I think Doug (the other answerer) has a point though, and I quote: "Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost." So pinging it would not make it a good solution. And I tried actually, cold start is still random...
– harrisonlo
Aug 12 '18 at 2:12
1
At low (ping) volumes, it's unlikely the service will attempt to scale with additional instances. Your question specified that you had no interest in alternative solutions and whether there is a way to keep an instance alive. This is the only solution to that problem currently.
– DazWilkin
Aug 12 '18 at 15:18
add a comment |
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2 Answers
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2 Answers
2
active
oldest
votes
active
oldest
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active
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votes
With all "serverless" compute providers, there is always going to be some form of cold start cost that you can't eliminate. Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost. Then, when load decreases, the unnecessary instances will be shut down.
There are ways to minimize your cold start costs, as you have discovered, but the costs can't be eliminated.
If you absolutely demand hot servers to handle requests 24/7, then you need to manage your own servers that run 24/7 (and pay the cost of those servers running 24/7). As you can see, the benefit of serverless is that you don't manage or scale your own servers, and you only pay for what you use, but you have unpredictable cold start costs associated with your project. That's the tradeoff.
add a comment |
With all "serverless" compute providers, there is always going to be some form of cold start cost that you can't eliminate. Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost. Then, when load decreases, the unnecessary instances will be shut down.
There are ways to minimize your cold start costs, as you have discovered, but the costs can't be eliminated.
If you absolutely demand hot servers to handle requests 24/7, then you need to manage your own servers that run 24/7 (and pay the cost of those servers running 24/7). As you can see, the benefit of serverless is that you don't manage or scale your own servers, and you only pay for what you use, but you have unpredictable cold start costs associated with your project. That's the tradeoff.
add a comment |
With all "serverless" compute providers, there is always going to be some form of cold start cost that you can't eliminate. Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost. Then, when load decreases, the unnecessary instances will be shut down.
There are ways to minimize your cold start costs, as you have discovered, but the costs can't be eliminated.
If you absolutely demand hot servers to handle requests 24/7, then you need to manage your own servers that run 24/7 (and pay the cost of those servers running 24/7). As you can see, the benefit of serverless is that you don't manage or scale your own servers, and you only pay for what you use, but you have unpredictable cold start costs associated with your project. That's the tradeoff.
With all "serverless" compute providers, there is always going to be some form of cold start cost that you can't eliminate. Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost. Then, when load decreases, the unnecessary instances will be shut down.
There are ways to minimize your cold start costs, as you have discovered, but the costs can't be eliminated.
If you absolutely demand hot servers to handle requests 24/7, then you need to manage your own servers that run 24/7 (and pay the cost of those servers running 24/7). As you can see, the benefit of serverless is that you don't manage or scale your own servers, and you only pay for what you use, but you have unpredictable cold start costs associated with your project. That's the tradeoff.
answered Aug 10 '18 at 15:50
Doug Stevenson
70.5k881101
70.5k881101
add a comment |
add a comment |
You're not the first to ask ;-)
The answer is to configure a remote service to periodically call your function so that the single|only instance remains alive.
It's unclear from your question but I assume your Function provides an HTTP endpoint. In that case, find a healthcheck or cron service that can be configured to make an HTTP call every x seconds|minutes and point it at your Function.
You may have to juggle the timings to find the Goldilocks period -- not too often that that you're wasting effort, not too infrequently that it dies -- but this is what others have done.
Thanks for answering! I think Doug (the other answerer) has a point though, and I quote: "Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost." So pinging it would not make it a good solution. And I tried actually, cold start is still random...
– harrisonlo
Aug 12 '18 at 2:12
1
At low (ping) volumes, it's unlikely the service will attempt to scale with additional instances. Your question specified that you had no interest in alternative solutions and whether there is a way to keep an instance alive. This is the only solution to that problem currently.
– DazWilkin
Aug 12 '18 at 15:18
add a comment |
You're not the first to ask ;-)
The answer is to configure a remote service to periodically call your function so that the single|only instance remains alive.
It's unclear from your question but I assume your Function provides an HTTP endpoint. In that case, find a healthcheck or cron service that can be configured to make an HTTP call every x seconds|minutes and point it at your Function.
You may have to juggle the timings to find the Goldilocks period -- not too often that that you're wasting effort, not too infrequently that it dies -- but this is what others have done.
Thanks for answering! I think Doug (the other answerer) has a point though, and I quote: "Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost." So pinging it would not make it a good solution. And I tried actually, cold start is still random...
– harrisonlo
Aug 12 '18 at 2:12
1
At low (ping) volumes, it's unlikely the service will attempt to scale with additional instances. Your question specified that you had no interest in alternative solutions and whether there is a way to keep an instance alive. This is the only solution to that problem currently.
– DazWilkin
Aug 12 '18 at 15:18
add a comment |
You're not the first to ask ;-)
The answer is to configure a remote service to periodically call your function so that the single|only instance remains alive.
It's unclear from your question but I assume your Function provides an HTTP endpoint. In that case, find a healthcheck or cron service that can be configured to make an HTTP call every x seconds|minutes and point it at your Function.
You may have to juggle the timings to find the Goldilocks period -- not too often that that you're wasting effort, not too infrequently that it dies -- but this is what others have done.
You're not the first to ask ;-)
The answer is to configure a remote service to periodically call your function so that the single|only instance remains alive.
It's unclear from your question but I assume your Function provides an HTTP endpoint. In that case, find a healthcheck or cron service that can be configured to make an HTTP call every x seconds|minutes and point it at your Function.
You may have to juggle the timings to find the Goldilocks period -- not too often that that you're wasting effort, not too infrequently that it dies -- but this is what others have done.
answered Aug 10 '18 at 15:30
DazWilkin
1,65921525
1,65921525
Thanks for answering! I think Doug (the other answerer) has a point though, and I quote: "Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost." So pinging it would not make it a good solution. And I tried actually, cold start is still random...
– harrisonlo
Aug 12 '18 at 2:12
1
At low (ping) volumes, it's unlikely the service will attempt to scale with additional instances. Your question specified that you had no interest in alternative solutions and whether there is a way to keep an instance alive. This is the only solution to that problem currently.
– DazWilkin
Aug 12 '18 at 15:18
add a comment |
Thanks for answering! I think Doug (the other answerer) has a point though, and I quote: "Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost." So pinging it would not make it a good solution. And I tried actually, cold start is still random...
– harrisonlo
Aug 12 '18 at 2:12
1
At low (ping) volumes, it's unlikely the service will attempt to scale with additional instances. Your question specified that you had no interest in alternative solutions and whether there is a way to keep an instance alive. This is the only solution to that problem currently.
– DazWilkin
Aug 12 '18 at 15:18
Thanks for answering! I think Doug (the other answerer) has a point though, and I quote: "Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost." So pinging it would not make it a good solution. And I tried actually, cold start is still random...
– harrisonlo
Aug 12 '18 at 2:12
Thanks for answering! I think Doug (the other answerer) has a point though, and I quote: "Even if you are able to keep a single instance alive by pinging it, the system may spin up any number of other instances to handle current load. Those new instances will have a cold start cost." So pinging it would not make it a good solution. And I tried actually, cold start is still random...
– harrisonlo
Aug 12 '18 at 2:12
1
1
At low (ping) volumes, it's unlikely the service will attempt to scale with additional instances. Your question specified that you had no interest in alternative solutions and whether there is a way to keep an instance alive. This is the only solution to that problem currently.
– DazWilkin
Aug 12 '18 at 15:18
At low (ping) volumes, it's unlikely the service will attempt to scale with additional instances. Your question specified that you had no interest in alternative solutions and whether there is a way to keep an instance alive. This is the only solution to that problem currently.
– DazWilkin
Aug 12 '18 at 15:18
add a comment |
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