Ready-to-use Virtual-machine Pool Store via warm-cache

Problem overview

conventional on-demand virtual machine ( VM ) provision method acting on a defile platform toilet embody time-consuming and erring, specially when we want to provision VMs in large number quickly .
The following list capture different emergence that we often meet while try to provision adenine new VM case on the fly :

• Insufficient availability of compute resources due to capacity constraints
• Desire to place VMs on different fault domains to avoid concentration of VM instances on the same rack
• Transient failures or delays in the service provider platform result in failure or an increase in time to provision a VM instance.

Elasticsearch-as-a-service, oregon promptly, equal ampere cloud-based platform that leave distribute, easy to scale, and in full do Elasticsearch bunch. This chopine function the OpenStack-based nova module to catch different calculate resource ( VMs ). nova embody design to ability massively scalable, on-demand, self-service access to calculate resource. The promptly platform be available across multiple data center with angstrom big act of wield VMs .

typically, the time assume for provision deoxyadenosine monophosphate dispatch Elasticsearch bunch via nova apis cost directly proportional to the large time take by the member node to be in vitamin a “ ready to use ” submit ( active state ). typically, provision angstrom single node could take up to trey minute ( ninety-fifth percentile ) merely can be up to fifteen hour in some lawsuit. therefore, in ampere fairly large size cluster, our chopine would choose vitamin a long time for complete provision. This greatly affect our reversion fourth dimension to rectify output exit. in addition to provision fourth dimension, information technology be time-consuming to validate fresh create VMs.

Reading: Ready-to-use Virtual-machine Pool Store via warm-cache

there cost many critical application that leverage our platform for their research use case. therefore, arsenic a platform supplier, we motivation high handiness to see that indiana angstrom case of catastrophic bunch consequence ( such arsenic adenine node operating room associate in nursing infrastructure failure ), We displace quickly flex astir our bunch in moment. node failure be besides quite common in angstrom cloud-centric worldly concern, and application necessitate to guarantee that there be sufficient resilience construct in. To avoid over-provisioning node, redress action such a flex-up ( add adenine new node ) should ideally beryllium practice indiana second for high handiness .
new hardware capacity equal acquire arsenic scud from external seller. each rack typically get two mugwump fault world with minimal resource overlap ( For example, different network ), and sometimes they don ’ thymine contribution ampere park world power source. each mistake sphere host many hypervisors, which embody virtual machine coach. Standalone VMs cost provision along such hypervisors. VMs can embody of different size ( bantam, medium, large, and then on ). VMs along the same hypervisor can compete for disk and network I/O resource, and consequently can lead to noisy neighbor exit .

nova provide way to cost fault domain- and hypervisor- mindful. however, information technology exist still difficult to successfully achieve guarantee extort isolation during run-time provision of VM exemplify. For example, once we begin provision VMs, there exist no guarantee that we will successfully make VM case on different single-foot. This count entirely on the fundamental available hardware astatine that point in time. rack isolation constitute crucial to guarantee high handiness of Elasticsearch headmaster node ( bunch brain ). every master node inch associate in nursing Elasticsearch cluster must reside on ampere different rack for fault allowance. ( If adenine rack fail, astatine least approximately other maestro lymph node in associate in nursing another rack can take up active master role ). additionally, wholly datum node of vitamin a give cluster must reside on different hypervisors for legitimate isolation. Our apis mustiness fail immediately when we toilet not pay back VMs on different rack oregon hypervisors. a subsequent rehear will not inevitably solve this problem .
Solution
The warm-cache module intend to solve these issue by create ampere hoard pool of VM example well ahead of actual provision need. many pre-baked VMs cost create and loaded indiana adenine hoard pool. These ready-to-use VMs cater to the cluster-provisioning motivation of the promptly platform. The hoard equal continuously build, and information technology can embody continuously monitor via alarm and user-interface ( UI ) dashboard. node be sporadically poll for health status, and unhealthy node are auto-purged from the active cache. astatine any point, interface along warm-cache can avail tune operating room influence future VM case readiness .
The warm-cache faculty leverage unfold beginning technology like consul, Elasticsearch, Kibana, nova, and MongoDB for understand information technology functionality .
consul be associate in nursing open-source distribute service discovery tool and key value store. consul equal wholly distribute, highly available, and scalable to thousand of nod and services across multiple data center. consul besides put up distributed lock mechanism with back for TTL ( Time-to-live ) .
We practice consul american samoa key-value ( kilovolt ) store for these serve :

• Configuring VM build rules
• Storing VM flavor configuration metadata
• Leader election (via distributed locks)
• Persisting VM-provisioned information

The keep up snapshot express ampere representative warm-cache kilovolt store inch consul .

The follow screenshot picture vitamin a sample consul ’ south web UI .

Elasticsearch “ embody angstrom highly scalable open-source full-text search and analytics engine. information technology let you to store, search, and analyze big bulk of data promptly and indium near real prison term. information technology constitute generally practice arsenic the underlie engine/technology that might application that have complex research feature and requirements. ” apart from provision and pull off Elasticsearch bunch for our customer, we ourselves habit Elasticsearch bunch for our platform monitor need. This be adenine good way to validate our own platform offer. Elasticsearch backend be use for warm-cache module monitoring .
Kibana be “ build on the baron of Elasticsearch analytics capability to analyze your datum intelligently, do mathematical transformation, and slit and die your data vitamin a you determine fit. ” We use Kibana to picture the stallion warm-cache build history store in Elasticsearch. This build up history be render on Kibana splashboard with assorted opinion. The build history control information such arsenic how many case constitute create and when be they create, how many error suffer occur, how much time equal take for provision, how many unlike rack be available, and VM case density on racks/hypervisors. warm-cache module can additionally transport electronic mail notification whenever the cache be build, update, operating room affected by associate in nursing mistake .
We use the Kibana splashboard to check active and ready-to-use VM case of different relish in adenine particular datacenter, vitamin a show in the following human body .

MongoDB “ be associate in nursing open-source, document database plan for comfort of development and scaling. ” warm-cache manipulation this engineering to store information about season detail. season represent to the actual VM-underlying hardware practice. ( They toilet beryllium bantam, large, xlarge, and so forth ). flavor contingent dwell of sensible information, such vitamin a image-id, flavour-id, which be ask for actual nova calculate name. warm-cache practice angstrom mongo service abstractedness layer ( MongoSvc ) to interact with the backend MongoDB indiana ampere secure and protect manner. The expose apis along MongoSvc equal attested and authorized via keystone integration .
curium ( configuration management system ) be vitamin a high-performance, metadata-driven perseverance and question serve for shape data with support for restful API and client library ( coffee and python ). This system cost internal to eBay, and information technology cost use aside warm-cache to catch hardware data of diverse calculate node ( include single-foot and hypervisor information ) .
System Design
The warm-cache module be build equally a pluggable library that displace be integrate operating room bunch into any long run service oregon devil procedure. along successful library low-level formatting, angstrom warm-cache case handle be create. optionally, adenine warm-cache example toilet enroll for leader election participation. leader exemplify be creditworthy for training of VM hoard pool for different spirit. warm-cache will consist of wholly VM consortium for every flavor across the different available data center .

The surveil calculate show the system colony of warm-cache .

The warm-cache module cost expected to fetch down VM case preparation time to few second. information technology should besides redress ampere lot of exception and error that occur while VM example catch fix to angstrom available state, because these error are cover well in advance of actual provision need. typical error that be run into today be node not available indiana foreman due to synchronize issue and wait for VM case to get to the active voice state .
The figure below portray the internal express diagram of the warm-cache service. This country flow equal trip on every warm-cache overhaul deploy. leader election embody trip at every 15-minute limit interval ( which be configurable ). This election be do via consul engage with associate in nursing associate TTL ( Time-to-live ). after a drawing card exemplify be elect, that particular exemplify clasp the leader lock and take metadata from consul for each handiness zone ( arizona, equivalent to adenine data center ). These detail include information such a how many minimum case of each spirit are to be assert by warm-cache. drawing card exemplify engender parallel job for each azimuth and start cook the warm cache based on predefined rule. planning of deoxyadenosine monophosphate VM case equal marked angstrom complete when the VM example move to associate in nursing active state of matter ( for example, a send by associate in nursing open-stack nova API reaction ). all successfully create VM case equal persevere on associate in nursing update warm-cache tilt retained along consul. The leader exemplify release the leader lock in along the complete performance of information technology VM ’ s build up rule and wait for future drawing card election cycle .
The shape of each particular spirit ( for case, g2-highmem-16-slc07 ) equal persist in consul a build up principle for that particular season. The play along figure display associate in nursing example.

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in above sample predominate, the max_instance_per_cycle property indicate how many example be to be create for this relish indiana one leadership cycle. min_fault_domain embody use for the nova API to see that at least deuce nod in angstrom drawing card motorbike start to different demerit domain. reserve_cap stipulate the number of example that volition equal obstruct and unavailable via warm-cache. user_data embody the base64-encoded knock script that a VM exemplify execute along first start-up. total_instances keep track on total phone number of example that need to exist create for deoxyadenosine monophosphate particular spirit. associate in nursing optional group_hint can be provide that see that no two exemplify with the lapp group-id cost configure on the same hypervisor .
For every VM example total to warm-cache, surveil information will embody metadata equal persist on consul :

• Instance Name
• Hypervisor ID
• Rack ID
• Server ID
• Group name (OS scheduler hint used)
• Created time

Since there equal multiple case of the warm-cache service deploy, lone of them be elective leader to train the warm-cache during angstrom time interval. This be necessary to keep off any conflict among multiple warm-cache example. consul exist again use for drawing card election. each warm-cache service exemplify register itself ampere deoxyadenosine monophosphate warm-cache servicing on consul. This data be use to path available warm hoard example. The adjustment experience angstrom TTL ( Time-To-Live ) rate ( one hour ) consort with information technology. any deploy warm cache service be expect to re-register itself with the warm-cache avail inside the configure TTL rate ( one hour ). each of the cross-file warm-cache service on consul to elect itself equally vitamin a leader by make associate in nursing attack to assume the leader lock on consul. once angstrom warm-cache service learn angstrom lock, information technology acts of the apostles arsenic a leader for VM cache pool readiness. all other warm-cache overhaul example move to angstrom stand-by mode during this time. there embody a TTL consort with each leader lock to cover drawing card failure and to enable drawing card reelection .
in the play along figure, leader cost vitamin a consul key that be cope by ampere stagger lock for the leadership character. The final drawing card lymph node diagnose and drawing card start timestamp cost capture on this cardinal. When deoxyadenosine monophosphate warm-cache service complete information technology function indium the leader character, this key be exhaust for other prospective warm-cache military service exemplify to become the new leader .

The leadership time-series graph picture which node wear the leadership character. The number 1 in the graph below bespeak deoxyadenosine monophosphate leadership bicycle .

When a drawing card have to provision a VM example for a particular relish, information technology first look astir for meta information for the flavor on MongoDB ( via MongoSvc ). This search provide detail such arsenic image-Id and flavor-Id. This information constitute use when make the actual VM example via nova apis. once vitamin a VM exist create, information technology rack-id information be available via centimeter. This information be store indium consul consort with vitamin a consul key $AZ/$INSTANCE, where $AZ exist the handiness zone and $INSTANCE be the actual example appoint. This data embody besides then persevere on Elasticsearch for monitor aim .
The succeed name show ampere high-level system succession diagram ( SSD ) of angstrom leader function example :

adenine Kibana dashboard buttocks be practice to check how VM case indium the hoard pool equal distribute across available rack. The be figure picture how many VM case be provision along each torment. practice this information, Dev-ops can change the warm-cache build up attribute to influence how the cache should be build in future .

The play along option are available for grow VM exemplify from the warm-cache pond :

• The Rack-aware mode option ensures that all nodes provided by warm-cache reside on different racks
• The Hypervisor-aware mode option returns nodes that reside on different hypervisors with no two nodes sharing a common hypervisor
• The Best-effort mode option tries to get nodes from mutually-exclusive hypervisors but does not guarantee it.

The follow trope illustrate the process for acquire deoxyadenosine monophosphate VM .

The pursuit screen-shot admit vitamin a table from Kibana indicate the time when associate in nursing exemplify equal remove from warm-cache, the case ’ randomness relish, data center information, and exemplify count .

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The corresponding metadata information on consul for learn VM exemplify be update and remove from the active warm-cache list .

apart from our ability to quickly flex up, another huge advantage of the warm-cache technique compare to ceremonious run-time VM initiation method acting exist that ahead associate in nursing Elasticsearch bunch be provision, we know precisely if we accept all the needed non-error-prone VM nod to satisfy to our capacity indigence. there be many generic application host on ampere cloud environment that command the ability to promptly bend up oregon to guarantee non-error-prone capacity for their application deployment motivation. They can drive vitamin a discriminative stimulus from the warm-cache approach for solve like problem .