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https://github.com/TritonDataCenter/manta

Manta is a scalable HTTP-based object store
https://github.com/TritonDataCenter/manta

distributed high-availability storage

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Manta is a scalable HTTP-based object store

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# Manta: a scalable, distributed object store



Manta is an open-source, scalable, HTTP-based object store. All the pieces

required to deploy and operate your own Manta are open source. This repo

provides documentation for the overall Manta project and pointers to the other

repositories that make up a complete Manta deployment.



## Getting started



The fastest way to get started with Manta depends on what exactly one

wishes to do.



* To use Manta see the [Getting Started](./docs/user-guide/#getting-started)

  section of the User Guide.



* To learn about installing and operating your own Manta deployment, see the

  [Manta Operator Guide](./docs/operator-guide/).



* To understand Manta's architecture, see [Bringing Arbitrary Compute to

  Authoritative Data](http://queue.acm.org/detail.cfm?id=2645649), the [ACM

  Queue](http://queue.acm.org/) article on its design and implementation.



* To understand the [CAP tradeoffs](http://en.wikipedia.org/wiki/CAP_theorem) in Manta,

  see [Fault Tolerence in Manta](http://dtrace.org/blogs/dap/2013/07/03/fault-tolerance-in-manta/) --

  which received [some notable praise](https://twitter.com/eric_brewer/status/352804538769604609).



* For help with working on Manta and building and testing your changes,

  see the [developer guide](docs/developer-guide)



## Community



Community discussion about Manta happens in two main places:



* The *manta-discuss*

  [mailing list](https://mantastorage.topicbox.com/groups/manta-discuss).

  If you wish to send mail to the list you'll need to join, but you can view

  and search the archives online without being a member.



* In the *#manta* IRC channel on the

  [Libera.chat IRC network](https://libera.chat/).



## Dependencies



Manta is composed of a number of services that deploy on top of Joyent's

[Triton DataCenter](https://github.com/TritonDataCenter/triton) platform (just "Triton"

for short), which is also open-source. Triton provides services for operating

physical servers (compute nodes), deploying services in containers, monitoring

services, transmitting and visualizing real-time performance data, and a bunch

more. Manta primarily uses Triton for initial deployment, service upgrade, and

service monitoring.



Triton itself depends on [SmartOS](http://smartos.org).  Manta also directly

depends on several SmartOS features, notably ZFS.



## Building and Deploying Manta



Manta service images are built and packaged using the same mechanisms as

building the services that are part of Triton. Once you have Triton set up,

follow the instructions in the [Manta Operator Guide](./docs/operator-guide/)

to deploy Manta.  The easiest way to play around with your own Manta

installation is to first set up a Triton cloud-on-a-laptop (COAL) installation

in VMware and then follow those instructions to deploy Manta on it.



If you want to deploy your own builds of Manta components, see "Deploying your

own Manta Builds" below.



## Repositories



This repository is just a wrapper containing documentation about Manta.  Manta

is made up of several components from many repositoies. This section highlights

some of the more important ones.



A full list of repositories relevant to Manta is maintained in a [repo manifest

file](./tools/jr-manifest.json) in this repo. To more conveniently list those

repos, you can use the [`jr` tool](https://github.com/TritonDataCenter/joyent-repos#jr).



The front door services respond to requests from the internet at large:



* [muppet](https://github.com/TritonDataCenter/muppet): the haproxy-based "loadbalancer"

  service

* [muskie](https://github.com/TritonDataCenter/manta-muskie): the node.js-based "webapi"

  service, this is Manta's "Directory API"

* [buckets-api](https://github.com/TritonDataCenter/manta-buckets-api): Node.js-based

  "buckets-api" service, this is Manta's "Buckets API"



The metadata tiers for the Directory and Buckets APIs store the entire object

namespace (not object data) as well as backend storage system capacity:



* [manatee](https://github.com/TritonDataCenter/manatee): the "postgres" service, a

  high-availability postgres cluster using synchronous replication and automatic

  fail-over

* [moray](https://github.com/TritonDataCenter/moray): Node-based key-value store built on

  top of manatee.  Also responsible for monitoring manatee replication topology

  (i.e., which postgres instance is the master).

* [electric-moray](https://github.com/TritonDataCenter/electric-moray): Node-based service

  that provides the same interface as Moray, but which directs requests to one

  or more Moray+Manatee *shards* based on hashing the Moray key.

* [buckets-mdapi](https://github.com/TritonDataCenter/manta-buckets-mdapi): a Rust-based

  API for managing all metadata for the Buckets API

* [buckets-mdplacement](https://github.com/TritonDataCenter/manta-buckets-mdplacement): a

  Rust-based API for handling routing of Buckets API objects to appropriate

  nodes in the storage tier.



The storage tier is responsible for actually storing bits on disk:



* [mako](https://github.com/TritonDataCenter/manta-mako): the "storage" service, a

  nginx-based server that receives PUT/GET requests from the front door services

  to store object data on disk

* [minnow](https://github.com/TritonDataCenter/manta-minnow): a Node-based agent that

  runs inside storage instances to periodically report storage capacity to the

  metadata tier



There are a number of services not part of the data path that are critical for

Manta's operation. For example:



* [binder](https://github.com/TritonDataCenter/binder): hosts both ZooKeeper (used for

  manatee leader election and for group membership) and a Node-based DNS server

  that keeps track of which instances of each service are online at any given

  time

* [mahi](https://github.com/TritonDataCenter/mahi): The "authcache" service for handling authn/authz.



Most of the above components are *services*, of which there may be multiple

*instances* in a single Manta deployment. Except for the last category of

non-data-path services, these can all be deployed redundantly for availability

and additional instances can be deployed to increase capacity.



For more details on the architecture, including how these pieces actually fit

together, see the [Architecture](./docs/operator-guide/architecture.md) section

of the Operator Guide.



## Deploying your own Manta Builds



As described above, as part of the normal Manta deployment process, you start

with the "manta-deployment" zone that's built into Triton.  Inside that zone, you

run "manta-init" to fetch the latest Joyent build of each Manta component.  Then

you run Manta deployment tools to actually deploy zones based on these builds.



The easiest way to use your own custom build is to first deploy Manta using the

default Joyent build and *then* replace whatever components you want with your

own builds.  This will also ensure that you're starting from a known-working set

of builds so that if something goes wrong, you know where to start looking.  To

do this:



1. Complete the Manta deployment procedure from the operator guide.

2. Build a zone image for whatever zone you want to replace.  See the

   instructions for building [Triton](https://github.com/TritonDataCenter/triton)

   zone images.  Manta zones work the same way.  The output of this process

   will be a zone **image**, identified by uuid.  The image is comprised of

   two files: an image manifest (a JSON file) and the image file itself

   (a binary blob).

3. Import the image into the Triton DataCenter that you're using to deploy Manta.

   (If you've got a multi-datacenter Manta deployment, you'll need to import the

   image into each datacenter separately using this same procedure.)

    1. Copy the image and manifest files to the Triton headnode where the Manta

       deployment zone is deployed.  For simplicity, assume that the

       manifest file is "/var/tmp/my_manifest.json" and the image file is

       "/var/tmp/my_image".  You may want to use the image uuid in the filenames

       instead.

    2. Import the image using:



           sdc-imgadm import -m /var/tmp/my_manifest.json -f /var/tmp/my_image



4. Now you can use the normal Manta zone update procedure (from the operator

   guide). This involves saving the current configuration to a JSON

   file using "manta-adm show -sj > config.json", updating the configuration

   file, and then applying the changes with "manta-adm update < config.json".

   When you modify the configuration file, you can use your image's uuid in

   place of whatever service you're trying to replace.



If for some reason you want to avoid deploying the Joyent builds at all, you'll

have to follow a more manual procedure.  One approach is to update the SAPI

configuration for whatever service you want (using sdc-sapi -- see

[SAPI](https://github.com/TritonDataCenter/sdc-sapi)) *immediately after* running

manta-init but before deploying anything.  Note that each subsequent

"manta-init" will clobber this change, though the SAPI configuration is normally

only used for the initial deployment anyway.  The other option is to apply the

fully-manual install procedure from the Operator Guide (i.e., instead of

using manta-deploy-coal or manta-deploy-lab) and use a custom "manta-adm"

configuration file in the first place.  If this is an important use case, file

an issue and we can improve this procedure.



The above procedure works to update Manta *zones*, which are most of the

components above.  The other two kinds of components are the *platform* and

*agents*.  Both of these procedures are documented in the Operator Guide,

and they work to deploy custom builds as well as the official Joyent builds.



## Contributing to Manta



To report bugs or request features, you can submit issues to the Manta project

on Github.  If you're asking for help with Joyent's production Manta service,

you should contact Joyent support instead.



See the [Contribution Guidelines](./CONTRIBUTING.md) for information about

contributing changes to the project.



## Design principles



Manta assumes several constraints on the data storage problem:



1. There should be one *canonical* copy of data.  You shouldn't need to copy

   data in order to analyze it, transform it, or serve it publicly over the

   internet.

2. The system must scale horizontally in every dimension.  It should be possible

   to add new servers and deploy software instances to increase the system's

   capacity in terms of number of objects, total data stored, or compute

   capacity.

3. The system should be general-purpose.

4. The system should be strongly consistent and highly available.  In terms of

   [CAP](http://en.wikipedia.org/wiki/CAP_theorem), Manta sacrifices

   availability in the face of network partitions.  (The reasoning here is that

   an AP cache can be built atop a CP system like Manta, but if Manta were AP,

   then it would be impossible for anyone to get CP semantics.)

5. The system should be transparent about errors and performance.  The public

   API only supports atomic operations, which makes error reporting and

   performance easy to reason about.  (It's hard to say anything about the

   performance of compound operations, and it's hard to report failures in

   compound operations.)  Relatedly, a single Manta deployment may span multiple

   datacenters within a region for higher availability, but Manta does not

   attempt to provide a global namespace across regions, since that would imply

   uniformity in performance or fault characteristics.



From these constraints, we define some design principles:



1. Manta presents an HTTP interface (with REST-based PUT/GET/DELETE operations)

   as the primary way of reading and writing data.  Because there's only one

   copy of data, and some data needs to be available publicly (e.g., on the

   internet over standard protocols), HTTP is a good choice.

2. Manta is an *object store*, meaning that it only provides PUT/GET/DELETE for

   *entire objects*.  You cannot write to the middle of an object or append to

   the end of one.  This constraint makes it possible to guarantee strong

   consistency and high availability, since only the metadata tier (i.e., the

   namespace) needs to be strongly consistent, and objects themselves can be

   easily replicated for availability.



It's easy to underestimate the problem of just reliably storing bits on disk.

It's commonly assumed that the only components that fail are disks, that they

fail independently, and that they fail cleanly (e.g., by reporting errors).  In

reality, there are a lot worse failure modes than disks failing cleanly,

including:



* disks or HBAs dropping writes

* disks or HBAs redirecting both read and write requests to the wrong physical

  blocks

* disks or HBAs retrying writes internally, resulting in orders-of-magnitude

  latency bubbles

* disks, HBAs, or buses corrupting data at any point in the data path



Manta delegates to ZFS to solve the single-system data storage problem.  To

handle these cases,



* ZFS stores block checksums *separately* from the blocks themselves.

* Filesystem metadata is stored redundantly (on separate disks).  Data is

  typically stored redundantly as well, but that's up to user configuration.

* ZFS is aware of how the filesystem data is stored across several disks.  As a

  result, when reads from one disk return data that doesn't match the expected

  checksum, it's able to read another copy and fix the original one.



## Further reading



For background on the overall design approach, see ["There's Just No Getting

Around It: You're Building a Distributed

System"](http://queue.acm.org/detail.cfm?id=2482856).



For information about how Manta is designed to survive component failures and

maintain strong consistency, see [Fault tolerance in

Manta](http://dtrace.org/blogs/dap/2013/07/03/fault-tolerance-in-manta/).



For information on the latest recommended production hardware, see [Joyent

Manufacturing Matrix](http://eng.joyent.com/manufacturing/matrix.html) and

[Joyent Manufacturing Bill of

Materials](http://eng.joyent.com/manufacturing/bom.html).