Ongoing Incident in Google Cloud(status.cloud.google.com) |
Ongoing Incident in Google Cloud(status.cloud.google.com) |
gcp should be designed in a way where the term “global outage” isn’t a word in their vocabulary.
In my company we are split in 3, US, EU, APAC, and we have the same issue with global outage for stuff we could have just managed regionally. For all the savings of the global architecture, they disappear each minute a client is down on a global outage because a guy thousands of kms away messed up.
You dont have to unify, at all. You dont unify with your competitors, and the world has not exploded: compete internally between regions ?
As far as global services go though, it's easy enough to say "it should just not be possible", but how do you propose doing that in practice for a global service?
How does new config going to go out, globally, without being global? How do global services work if they're not global? How does DDoS protection work if you don't do it globally?
People make fun of "webscale" but operating Google is really difficult and complicated!
As I understand it, GCP is already designed to make global outages impossible. Obviously this outage shows that they messed up somehow and some global point of failure still remains. Looking forward to the post-mortem.
How much more work would Google create for themselves if they had not globalized their stack? Are we talking something like 5 subsets to manage instead of 1?
Ex-googler, no particular knowledge of this event, information might be out of date.
Of course, if you deploy a change to all of your separated stacks at once through some sort of automated pipeline it doesn’t matter too much. Easy to break everything simultaneously that way if there’s some difference between test and prod you didn’t realize was there.
I reckon the only to achieve that would be to have the same level of interoperability between regions as you would get between two distinct cloud providers.
Of course, at Google scale 'partial' is still very big.
And why enterprises clamoring for AWS to feature match Google's global stuff (theoretically making I.T. easier) instead of remaining regionally isolated (making I.T. actually more resilient, without extra work if I.T. operators can figure out infra-as-code patterns) should STFU and learn themselves some Terraform, Pulumi, or etc.
Also, AWS, if you're in this thread, stop with the recent cross-region coupling features already. Google's doing it wrong, explain that, and be patient, the market share will come back to you when they run out of the GCP subsidy dollars.
> gcp should be designed in a way where the term “global outage” isn’t a word in their vocabulary.
Listening to the “All In Podcast” yesterday even those guys were talking about revenue drops in the big cloud services and noting we’re currently in the midst of a swing back to self-hosting/co-location/whatever thinking and migrations out.
IMHO those building greenfield solution today should take a hard look at whether the default approach from the last ~10 years “of course you build in $BIGCLOUD” makes sense for the application - in many cases it does not.
It also has the added benefit of de-centralizing the internet a bit (even if only a little).
<3 To the engineers trying to fix it at the moment.
Not great, not terrible.
https://arstechnica.com/tech-policy/2023/02/us-says-google-r...
They claim the Gmail specific issues are resolved. We shall see...
Feb 27, 2023 2:03 PM UTC We experienced a brief network outage with package loss, impacting a number of workspace services. The impact is over. We are investigating and monitoring.
I would be hesitant to attribute slowed growth to a return to self hosting, it's much more likely that it's caused by companies dialing back their cloud growth after spending a few years going ham digitizing everything during the pandemic.
From that pov I expect my platform to behave like a utility (never change or only change with strict backward compatibility). That level of control simply is against the business model of the cloud.
That said I think the point generally remains - one could argue slower than expected growth in cloud services is a revenue drop (in a way) vs expectations. The market responded accordingly[0] - "However, Azure growth is decelerating." Note that this is all including the explosion in "2023 AI hotness" which is almost certainly offsetting what would be larger losses due to the shift I'm arguing. As the All In Guys noted "you won't see a pitch deck without the letters AI in it" - and a good chunk of that is still going to cloud providers as (in my opinion) there are long tails to these changes and many existing solutions/applications getting "AI" slapped on them are effectively trapped in $BIGCLOUD.
Self-hosting AI is also significantly more difficult and upfront more expensive when you start looking at dealing with (typically) Nvidia hardware costs and software stack complexity. I can definitely see many of these "pivots" to "something AI, we need to throw AI in this" the more well understood and initially faster and "cheaper" utilization of cloud services will continue until the AI trend stabilizes.
From what I could hear (and process) over the screaming the All In Guys presented the argument I tend to agree with - a resurgence of self-hosted infrastructure.
Companies are also dialing back cloud spend because they're realizing for many applications it's very expensive relatively and can actually be limiting compared to self-hosting[1]. Per usual when the cheap money and economic boom retracts they start actually looking at costs they were once happy to just keep writing checks for.
I'd like to reiterate there's a lot of calculation and strategy when it comes down to selecting infrastructure hosting. Again, I think we're in a period where there's a bit of a sea change/wakeup from the past decade of "of course you always build and host everything in $BIGCLOUD" - without even remotely considering alternatives. It's been the default for a while and it isn't as much anymore - and I'd argue that trend is accelerating. There is no "one size fits all".
[0] - https://www.investors.com/news/technology/msft-stock-microso...
[1] - https://www.linkedin.com/pulse/snapchat-earnings-case-runawa...
You build greenfield in cloud precisely because it is greenfield and the utilization isn't well understood. Cloud options let you adjust and experiment quickly. Once a workload is well understood it's a good candidate for optimization, including a move to self managed hardware / on prem.
Buying hardware is a great option once you actually understand the utilization of your product. Just make sure you also have competent operators.
I would argue as the AI trend (eventually) wanes and many AI startups and projects within existing companies inevitably eventually fail to materialize the much longer and more general trend of migration out of $BIGCLOUD will be more drastic and obvious.
I don't buy individual stocks but I would happily bet a dinner on big cloud growth showing substantial reductions/losses in coming years as the overall situation stabilizes.
When one buys a house, they should take a hard loo at whether the default approach of paying for utilities makes sense, versus generating their own power.
While that's a bit snarky, the reasoning is similar. You can:
* Use "bigcloud"(TM) with the whole kit: VMs, their managed services, etc * Use bigcloud, but just VM or storage * Rent VMs from a smaller provider * Rent actual servers * Buy your servers and ship to a colo * Buy your servers and build a datacenter
Every level you drop, you need more work. And it grows(I suspect, not linearly). Sure, if you have all the required experts (or you rent them) you can do everything yourself. If not, you'll have to defer to vendors. You will pay some premium for this, but it's either that, or payroll.
What also needs to be factored in is how static your system is. If a single machine works for your use-case, great.
One of the systems I manage has hundreds of millions of dollars in contracts on the line, thousands of VMs. I do not care if any single VM goes down; the system will kill it and provision a new one. A big cloud provider availability zone often spans across multiple datacenters too, each datacenter with their own redundancies. Even if an entire AZ goes down, we can survive on the other two (with possibly some temporary degradation for a few minutes). If the whole region goes down, we fallback to another. We certainly don't have the time to discuss individual servers or rack and stack anything.
It does not come cheap. AWS specifically has egregious networking fees and you end up paying multiple times (AZ to AZ traffic, NAT gateways, and a myriad services that also charge by GB, like GuardDuty). It adds up if you are not careful.
From time to time, management comes with the idea of migrating to 'on-prem', because that's reportedly cheaper. Sure, ignoring the hundreds of engineers that will be involved in this migration, and also ignoring all the engineers that will be required to maintain this on-premises, it might be cheaper.
But that's also ignoring the main reason why cloud deployments tend to become so expensive: they are easy. Confronted with the option of spinning up more machines versus possibly missing a deadline, middle managers will ask for more resources. Maybe it's "just" 1k a month extra (those developers would cost more!). It gets approved. 50 other groups are doing the same. Now it's 50k. Rinse, repeat. If more emphasis would be placed into optimization, most cloud deployments could be shrunk spectacularly. The microservices fad doesn't help(your architecture might require that, but often the reason it does is because you want to ship your org chart, not for technical reasons).
Yes, people do. They install solar panels and use them to generate at least some of their own power. Near future battery tech might allow them to generate all of it if they get enough sunlight, in which case this will become a genuine question to answer: how much to install and maintain the panels and batteries over their lifetime, vs expected cost of purchasing power from utilities.
In a similar manner, cloud vs self hosting is a valid consideration that changes over time. We now have docker and similar tools which make managing your own infrastructure much easier than it was ten years ago. I fully expect even better tools will come out in the future so this consideration does change over time. Maybe in another ten years there'll be almost no benefit to using the cloud (except maybe as a CDN).
If one provider is down more than the others, the criticism is not only valid, it results in real business loss for the provider and its customers.
On multi-cloud: it's one way to reduce the amount of downtime you have, but it comes with a significant operational cost depending on how your application is architected and how your teams internal to your company are formed. It is totally practical for someone to bank on AWS' reliability until they're at a significant amount of traction or revenue where the added uptime of going multicloud is worth the investment. I know you're not saying this isn't the case (I think you're saying "do that if you're going to complain about 1 providers' uptime"), but thought it was worth putting the context into the HN ether.
Multi-cloud is saying you think you can manage Kafka across two or three clouds better than GCP can manage Pub/Sub.
Er, we absolutely can and should compare rates of problems and overall reliability.
If you run your own hardware these events are inevitable too.
I know it's just a psychological thing about giving up "control", but I have to stifle a chuckle every time.
Is anyone tracking reliability for these public providers? Would be curious how AWS compares to Azure and GCP. My experience is it's better, but we may have avoided Kinesis or whatever that keeps going down.
in multiple datacenters?
Let's take a gander at incident history: https://status.cloud.google.com/summary
Cloud Build looks bad... three multi-hour incidents this year, four in fall/winter last year.
Cloud Developer Tools have had four multi-hour incidents this year, many last fall/winter.
Cloud Firestore looks abysmal... Six multi-hour incidents this year, one of them 23 hours.
Cloud App Engine had three multi-hour incidents this year, many in fall/winter last year.
BigQuery had three multi-hour incidents this year, many in fall/winter last year.
Cloud Console had five multi-hour incidents this year, many in fall/winter last year. (And from my personal experience, their console blows pretty much all the time)
Cloud Networking has had nine incidents this year, one of them was eight days long. What the fuck.
Compute Engine has had five multi-hour incidents this year, many last fall/winter.
GKE had 3 incidents this year, multiple the past winter.
Can somebody do a comparison to AWS? This seems shitty but maybe it's par for the course?
This is a pretty reductionist summary, e.g. the 8-day Cloud Networking incident root cause:
> Description: Our engineering team continues to investigate this issue and is evaluating additional improvement opportunities to identify effective rerouting of traffic. They have narrowed down the issue to one regional telecom service provider and reported this to them for further investigation. The connectivity problems are still mostly resolved at this point although some customers may observe delayed round trip time or longer latency or sporadic packet loss until fully resolved.
Still a big problem product-wise, but you're looking at a global incident history view without any region/severity filters.
The corresponding AWS service health dashboard makes it much harder to view this level of detail, but is also actually useful for someone asking "is product $xyz which I depend on in region $abc currently down or not"
(full disclosure, work at Google but not on cloud stuff)
Sure, companies are probably less interested in wacky new cloud features then they were before, but that means going back to basics like EC2 and RDS, which do function like utilities, not going back to their own data centers.
Public cloud will grow a lot more. I'd expect a slowdown when they're all ~10x what they are now.
Excellent point. AWS is 21 years old. Docker (essentially the foundation for most self-hosting these days) is 10 years old. I think we're going to see many more self-hosted K8s control planes (as one example). This isn't considering even more modern tools built on these fundamental components that make self-hosting even easier.
The global outage thing seems to be a consistent "feature" of GCP - how are we supposed to architect our deployments if the regional isolation model is not a bulwark against high availability on GCP?
In the cloud, even very small scale apps can run into weird situations like the app server is up, the database is down, and the cache is responding about 50% of the time.
If you don't account for that from the beginning, it can lead to your app displaying some bizarre stuff to users.
I haven't run a server locally in 13 years but I can see why some people would miss it.
Can you share where you got this? Which numbers? I didn't think AWS (or any cloud provider) released details of their operation at that level of granularity.
As one example, the headline here is actually "Microsoft points to AI to drive the next wave of cloud, revenues"[0]. While not hard revenue breakout numbers Microsoft is investing heavily in OpenAI and rapidly (already) integrating it everywhere they can - search, Azure, etc. The investment, utilization, and published pricing are the numbers I'm talking about here.
The real hard numbers and position that supports my thesis (unsurprisingly) comes from Nvidia[1]. Since at least May 2022 Nvidia has been touting their revenues attributed to big cloud demand. Interestingly, Nvidia is rapidly moving to disintermediating big cloud in launching their own "AI cloud"[2]. It's going to be interesting to see how that shakes out...
Google has also been caught somewhat flat-footed and is simultaneously investing even more in "AI" with what will almost certainly be significant revenue opportunity with GCP. I don't follow AWS as closely but I don't see how they could be excluded from this trend - other than having first-mover advantage in cloud services with many more (at this point legacy) customers forever trapped in AWS.
I tend not to try to prognosticate on things like this but it's one of the rare instances I'm very confident in my thesis here. Obviously I'm just some random HN guy but like I said I'd make a friendly bet here.
People need to remember AWS is over 20 years old. There's not a good historical track record of any computing platform/architecture/approach maintaining a strangle hold much longer than that (except maybe Windows, which I'm not sure is comparable).
[0] - https://archive.is/tKLOz
[1] - https://www.reuters.com/technology/nvidia-forecasts-fourth-q...
[2] - https://www.crn.com/news/components-peripherals/nvidia-tease...
1. Some networking-related service has global, non-standard (compared to the rest of the company) configuration
2. The relevant VP is aware and has decided not to change it because that change is quoted as impossible
3. Some change elsewhere happens that assumes standard configuration
4. The networking service breaks and causes a global outage
5. VP is told to fix it
6. Fix rolls out in weeks, because it wasn't as hard as they said before
These constraints get thrown to the wind when the downtime is already happening.
However, I do think it will be at least "noticeable" in terms of individual customers with large spend. Total GCP revenue in 2022 was roughly 65 billion and Snap leaving alone is 1.5% of total revenue.
Especially looking at ML cases where cloud GPU pricing is wildly expensive - retail on-demand instance A100 pricing is at least $3/hr which practically speaking with the AWS pricing model is can be twice that all-in. This is for an instance with 32GB of RAM and 8 VCPUs - which for a lot of A100 use cases is useless. Need 32 vCPU and 256 GB of RAM? That's more like $20/hr.
A single A100 machine that's above and beyond more capable can be had from Dell for roughly $50k, which even factoring in hosting based on colo pricing I've seen has an ROI of ~15 months for constant usage. For the equivalent hardware (and still vastly improved performance - 32vCPU and 256GB of RAM) that ROI gets to less than six months.
Yes, the A100 is typically used for training (and cloud definitely still makes sense there) but more and more models require the performance and VRAM of a V100/H100 for inference (24/365 availability). Do it at any kind of scale/redundancy and ROI catches up even faster. An equivalent to this approach is reserved pricing, which over the 1-3yr term of a lease vs. reserved instance self-hosting becomes almost comically more cost and performance effective. With the extra benefit of actually being more flexible.
Financing and leasing is readily available and with various tax incentives (like Section 179 leasing) you can pretty quickly pay for a FTE to manage the infra for you - which is probably a wash anyway because at any kind of "real" scale or complexity you almost certainly already have dedicated human resources just to manage cloud. You don't even ever need for an employee to go to the hosting facility because most will rack and provision your hardware for free. Combined with remote hands and standard warranty support any (in my experience very rare) hardware failures just get handled.
I should note that this model almost eliminates the tendency for cloud spend to balloon to many X anticipated/budgeted spend - the all too common story of "sticker shock" from clouds on bandwidth alone that cloud has ridiculous markups on. Colo pricing and leases are fixed cost (with all you can eat port speed bandwidth included or so cheap at 95th percentile billing it's practically a rounding error).
I have significant experience at CTO level with both approaches (and hybrid, of course). In many situations the benefits of "self-hosting" vs cloud are dramatic.
The extremely effective marketing that has created and perpetuated an industry wide fear of self-hosting and hardware (especially with the "always cloud always" generation) is fading. I think the uptime and reliability promises of cloud are also fading - this thread started off with discussion of yet-another cloud outage. My background is in healthcare and telecom and I'm shocked at the cavalier attitude of just accepting these outages and being down while standing around helpless wondering when your big cloud will acknowledge, communicate, and resolve them. A few machines in a few rack units of space across a couple of facilities generally trounces cloud in reliability and uptime.
I love HN and the overall knowledge and quality of discussion here but when it comes to hardware and self-hosting many have completely drunk the cloud Kool-Aid and have zero experience with self-hosting - so no idea what they're talking about. Not saying you personally, just generally.
However even in these exceptional cases there are hidden costs that will likely arise.
For most companies the very concept of self hosting is comical. This is a one way train.
For an established real business there's almost no question.
Do you have any experience with self-hosting and examples of hidden costs? In my experience with both and hybrid approaches cloud has substantially more dramatic hidden costs. From a cost and pricing perspective cloud has many more foot guns - it's routine at this point for people to report exceeding their monthly budgets and billing notifications literally overnight.