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| <li><a class="reference internal" href="#id1" id="id2">Hardware</a><ul> |
| <li><a class="reference internal" href="#metrics" id="id3">Metrics</a></li> |
| <li><a class="reference internal" href="#write-proxy" id="id4">Write Proxy</a><ul> |
| <li><a class="reference internal" href="#cpus" id="id5">CPUs</a></li> |
| <li><a class="reference internal" href="#memories" id="id6">Memories</a></li> |
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| <div class="section" id="id1"> |
| <h2><a class="toc-backref" href="#id2">Hardware</a></h2> |
| <p>Figure 1 describes the data flow of DistributedLog. Write traffic comes to <cite>Write Proxy</cite> |
| and the data is replicated in <cite>RF</cite> (replication factor) ways to <cite>BookKeeper</cite>. BookKeeper |
| stores the replicated data and keeps the data for a given retention period. The data is |
| read by <cite>Read Proxy</cite> and fanout to readers.</p> |
| <p>In such layered architecture, each layer has its own responsibilities and different resource |
| requirements. It makes the capacity and cost model much clear and users could scale |
| different layers independently.</p> |
| <div class="figure align-center"> |
| <img alt="../images/costmodel.png" src="../images/costmodel.png" /> |
| <p class="caption">Figure 1. DistributedLog Cost Model</p> |
| </div> |
| <div class="section" id="metrics"> |
| <h3><a class="toc-backref" href="#id3">Metrics</a></h3> |
| <p>There are different metrics measuring the capability of a service instance in each layer |
| (e.g a <cite>write proxy</cite> node, a <cite>bookie</cite> storage node, a <cite>read proxy</cite> node and such). These metrics |
| can be <cite>rps</cite> (requests per second), <cite>bps</cite> (bits per second), <cite>number of streams</cite> that a instance |
| can support, and latency requirements. <cite>bps</cite> is the best and simple factor on measuring the |
| capability of current distributedlog architecture.</p> |
| </div> |
| <div class="section" id="write-proxy"> |
| <h3><a class="toc-backref" href="#id4">Write Proxy</a></h3> |
| <p>Write Proxy (WP) is a stateless serving service that writes and replicates fan-in traffic into BookKeeper. |
| The capability of a write proxy instance is purely dominated by the <em>OUTBOUND</em> network bandwidth, |
| which is reflected as incoming <cite>Write Throughput</cite> and <cite>Replication Factor</cite>.</p> |
| <p>Calculating the capacity of Write Proxy (number of instances of write proxies) is pretty straightforward. |
| The formula is listed as below.</p> |
| <pre class="literal-block"> |
| Number of Write Proxies = (Write Throughput) * (Replication Factor) / (Write Proxy Outbound Bandwidth) |
| </pre> |
| <p>As it is bandwidth bound, we'd recommend using machines that have high network bandwith (e.g 10Gb NIC).</p> |
| <p>The cost estimation is also straightforward.</p> |
| <pre class="literal-block"> |
| Bandwidth TCO ($/day/MB) = (Write Proxy TCO) / (Write Proxy Outbound Bandwidth) |
| Cost of write proxies = (Write Throughput) * (Replication Factor) / (Bandwidth TCO) |
| </pre> |
| <div class="section" id="cpus"> |
| <h4><a class="toc-backref" href="#id5">CPUs</a></h4> |
| <p>DistributedLog is not CPU bound. You can run an instance with 8 or 12 cores just fine.</p> |
| </div> |
| <div class="section" id="memories"> |
| <h4><a class="toc-backref" href="#id6">Memories</a></h4> |
| <p>There's a fair bit of caching. Consider running with at least 8GB of memory.</p> |
| </div> |
| <div class="section" id="disks"> |
| <h4><a class="toc-backref" href="#id7">Disks</a></h4> |
| <p>This is a stateless process, disk performances are not relevant.</p> |
| </div> |
| <div class="section" id="network"> |
| <h4><a class="toc-backref" href="#id8">Network</a></h4> |
| <p>Depending on your throughput, you might be better off running this with 10Gb NIC. In this scenario, you can easily achieves 350MBps of writes.</p> |
| </div> |
| </div> |
| <div class="section" id="bookkeeper"> |
| <h3><a class="toc-backref" href="#id9">BookKeeper</a></h3> |
| <p>BookKeeper is the log segment store, which is a stateful service. There are two factors to measure the |
| capability of a Bookie instance: <cite>bandwidth</cite> and <cite>storage</cite>. The bandwidth is majorly dominated by the |
| outbound traffic from write proxy, which is <cite>(Write Throughput) * (Replication Factor)</cite>. The storage is |
| majorly dominated by the traffic and also <cite>Retention Period</cite>.</p> |
| <p>Calculating the capacity of BookKeeper (number of instances of bookies) is a bit more complicated than Write |
| Proxy. The total number of instances is the maximum number of the instances of bookies calculated using |
| <cite>bandwidth</cite> and <cite>storage</cite>.</p> |
| <pre class="literal-block"> |
| Number of bookies based on bandwidth = (Write Throughput) * (Replication Factor) / (Bookie Inbound Bandwidth) |
| Number of bookies based on storage = (Write Throughput) * (Replication Factor) * (Replication Factor) / (Bookie disk space) |
| Number of bookies = maximum((number of bookies based on bandwidth), (number of bookies based on storage)) |
| </pre> |
| <p>We should consider both bandwidth and storage when choosing the hardware for bookies. There are several rules to follow: |
| - A bookie should have multiple disks. |
| - The number of disks used as journal disks should have similar I/O bandwidth as its <em>INBOUND</em> network bandwidth. For example, if you plan to use a disk for journal which I/O bandwidth is around 100MBps, a 1Gb NIC is a better choice than 10Gb NIC. |
| - The number of disks used as ledger disks should be large enough to hold data if retention period is typical long.</p> |
| <p>The cost estimation is straightforward based on the number of bookies estimated above.</p> |
| <pre class="literal-block"> |
| Cost of bookies = (Number of bookies) * (Bookie TCO) |
| </pre> |
| </div> |
| <div class="section" id="read-proxy"> |
| <h3><a class="toc-backref" href="#id10">Read Proxy</a></h3> |
| <p>Similar as Write Proxy, Read Proxy is also dominated by <em>OUTBOUND</em> bandwidth, which is reflected as incoming <cite>Write Throughput</cite> and <cite>Fanout Factor</cite>.</p> |
| <p>Calculating the capacity of Read Proxy (number of instances of read proxies) is also pretty straightforward. |
| The formula is listed as below.</p> |
| <pre class="literal-block"> |
| Number of Read Proxies = (Write Throughput) * (Fanout Factor) / (Read Proxy Outbound Bandwidth) |
| </pre> |
| <p>As it is bandwidth bound, we'd recommend using machines that have high network bandwith (e.g 10Gb NIC).</p> |
| <p>The cost estimation is also straightforward.</p> |
| <pre class="literal-block"> |
| Bandwidth TCO ($/day/MB) = (Read Proxy TCO) / (Read Proxy Outbound Bandwidth) |
| Cost of read proxies = (Write Throughput) * (Fanout Factor) / (Bandwidth TCO) |
| </pre> |
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