Architecture – how to design a high-availability application – software engineering stack exchange

• Our host sometimes experiences outages (as they all do), and we want to minimize the impact on our customers, so for instance, they would switch on datacenter B if datacenter A is down.

• When we upgrade the version, we shut down the site for maintenance, and it usually takes a few hours (migration scripts, etc). Database testing We’d like the users to have a more seamless transition, with as minimal a downtime as possible (they use server B while server A is being upgraded).

• Optionnaly, our customers are located around the world, and we want them to have the best experience possible despite their possibly crappy connections (anyone who worked with Indian devs should know what I mean). Database graph Ideally, we’d like to be able to plug a server in their office (or use a datacenter near their city), and it would integrate seamlessly into our architecture.

We don’t remotely need 99% availability, not even 95%. Database naming conventions It’s a documents management app. Database entity Nobody cares. Database developer But since migrations can take a while, and there are customers around the world, sometimes we prevent a customer from working for most of their day.

For the SQL part, even though there aren’t “proper” DBAs, we know about the SQL possibilities: replication, mirroring, etc. Data recovery plan On the DB side, it’s pretty easy to find resources for this. Data recovery kansas city What is harder is everything else: storing sessions, the code, etc. N k database If my webservice server goes down, how does my UI knows it must switch? How are my sessions persisted across servers?

Unfortunately, none of us have experience in this area, and we don’t even know where to start looking. Data recovery 2016 Are there best practices for this? Design patterns? Libraries (which should be free because we don’t have money)?

We’re using ASP.Net and SQL Server, with a WCF webservice in the middle. 510 k database fda We have a bunch of Windows services lying around, but they are not mission-critical, and I assume the methods to deal with the website will be applicable to the services.

I understand that most cloud platforms provide a built-in system for this, but cloud hosting is a no-go because of our sysadmin, who want to manage everything themselves and not rely on anyone.

Ideally, factor out any state, including session state into shared-state systems like a database or an in-memory session state server. Database programmer Depending on your application design this may cause performance issues due to the added latency getting a large amount of state.

If a single database can’t handle the load, leverage session state partitioning (or sharding or consistent hashing) to route particular request to a particular database box.

If factoring out state is too hard, you can go with server affinity for load balancing (ie users are consistently routed to the same box, often cookie based). Data recovery osx It’s not as highly available as a stateless round robin approach, because a box outage will impact all users & state on that that box, but it beats a complete outage (use-case dependent).

Design your database scripts in such a way that database upgrades can be done while the system is running, in other words, maintain backwards compatibility. Database integrity A pattern that works well for that is “expand, then contract” -> make only additive, backwards compatible changes but removing dependencies on the fields (etc) that you want to get rid of; then upgrade all clients of the database to v-latest; then do another db-upgrade to get rid of the old fields (etc) in the database. Database backup This can be a slow process if you have a large database and you have to be careful to not scupper the performance of your system.

Upgrading your app tier: since your not using a cloud environment, I recommend you follow the canary deployment pattern: do a rolling upgrade of your web & middle tier boxes. Hollywood u database If the deployment goes wrong, take the box out of the load balancer, just like you would as if it had failed.

Word of warning: evolving a system that hasn’t been designed for HA into one that is, can be a long and costly process. Data recovery ipad You’ll have to make trade-offs along the way (cost vs effort to reach a particular level of availability)

Your cloud paranoia is unwarranted – providers such as AWS in conjunction with good practice on your part can control / mitigate most risks – have a look at their compliance page to get a feel for what regulations they’re compliant with:

After realizing that trying to squeeze in any explanation might go very long so I will write down all the observations I have made. Database vs server Questioning the premise Cloud system is panacea

Even if you were to go fully on cloud, with a top cloud provider, you will still need to design your application for resilience, grounds up. Database is in transition AWS might replace your VM, but your application should be capable of restarting if left in the middle of computation. Data recovery ios We don’t want to use cloud system, because of x/y/z

Unless you are an ultra large organization, you are better-off using cloud systems. Database data types Top-3 cloud systems (AWS, MSFT, Google), employ thousands of engineers to give you promised SLAs and the easy to manage dashboard. Data recovery johannesburg Its actually a good bargain to use them in lieu of spending a dime on this in-house. Iphone 5 data recovery software Problems in scoping and design

Defining, quantifying and then continuously measuring the availability of a service is a bigger challenge than writing solution for availability issues. Database operations Defining and measuring ‘availability’ is harder than expected

Multiple stakeholders have a different view of availability, and what may happen is the definition preferred by a person with highest salary trumps other definition. Database index This is sometimes correct definition, but often the eco-system is not built around measuring the same thing because that ideal definition is much tricky to measure, let alone monitor in real time. Database crud If you have a definition of availability that can’t be monitored in real time, you will find your self-doing similar project again and again with eerie similarities.

Stick with something that makes sense and something that can be easily monitored. Drupal 8 database People underestimate the complexities of the always available system.

To address the elephant in the room, let me say this: “No multi-computer system is 100% available, it may in future but not with current technology.”

All comp-sci engineers worth their salt know distributed computing limitations, and most of them will not mention it in meetings, being afraid they will look like noobs.

To make up for all those who don’t mention distributed computing limitations I will say, its complicated but don’t always trust computers. Data recovery disk People overestimate their/their engineer’s capabilities

Unfortunately, availability falls in the category, where you don’t know what you want but you know what you don’t want. Database 3 tier architecture It is a bit trickier that ‘know the wants’ category such as UI.

It requires a little bit of experience and lot of reading to learn from other’s experience and some more. Data recovery orlando Building an available system from grounds-up

Make sure you will evangelize to every architecture and design team about the right priority of the availability as a system requirement. Database cardinality Attributes of system helping availability

Some examples of this are to never have only a single VM behind a VIP or never store only a single copy of your data. Database unit testing These are the questions that a good IAAS will make it easier for you to solve but you will still have to make these decisions. I data recovery software free download Modularity

A modular REST is better than monolithic SOA. O review database An even modular microservice is actually more available than the usual HATEOS REST. Database in recovery The reasoning could be found in Yield related discussion in next section.

If you are doing batch processing then better to batch processing in a reasonable batch of 10s compared to dealing with a batch of 1,000,000. Data recovery wizard professional Resiliency “I am always angry”

A resilient system is always ready to recover. Data recovery open source This resiliency applies to instances such as acknowledging ACK for a write only after writing to RAID disk, and possibly over at least two data centers.

Another latest trending is to use conflict-free data structures, where data structure assumes the responsibility to resolve conflicts when presented with two different versions.

A system can not be resilient as an afterthought, it has to be predicted and built-in. Gif database A failure is guaranteed over the long term, so we should be always prepared with a plan to recover. Data recovery lifehacker Log trail

This is technically a subtype of Resilience, but a very special one because of it’s catch all capabilities. Top 10 data recovery software 2014 Despite the best effort, we may not be able to predict the pattern of unavailability. Database gale If possible, maintain enough log trail of the system activities to be able to playback system events. Database life cycle This will, at great manual cost, allow you to recover from unforeseen situations. Data recovery dallas Attributes of availability

Do you must produce the most accurate possible answer or is it ok make mistakes? Just for a reference, when you withdraw money from ATM, it is not guaranteed to be correct. Data recovery usb If the bank finds out it made a mistake, it might you to reverse the transactions. Database 4th normal form If your system is producing prime numbers, then I would guess, you may want right answers all the time. V database in oracle Yield

Your answer may be correct at one point of time, but by the time the light has left the screen and entered the retina of the observer, things could have changed. Data recovery tampa Does it make your answer wrong? No, it just makes it inconsistent. R studio data recovery with crack Most applications are eventual consistent, but the trick is defining what kind of consistency model your application is going to provide.

A lot depends on what total impact of short-term effects(loss of revenue) and long term effects (ill reputation, customer retention). Database uses Depending upon customer type (paying/free, repeat/unique, captive) and resource availability different levels of availability guarantees should be built in. Database history Towards improving the availability of an existing system

Operational management of individual machines and a network is such complex, that I assume you have left it to the cloud provider or you are already expert enough to know what you are doing. Database b tree I will touch other topics under availability.

Since we agreed that operational management which would cover any physical infrastructure management, ought to be done by professionals I will touch other causes of unavailability for completeness sake.

IMO availability should also include lack of expected behavior, meaning if the user is not shown expected experience, then something is unavailable. Database optimization With that broad definition in mind, the following could cause unavailability: