Pricing review: Lambda

Pricing review: DynamoDB

On-Demand

Provisioned

WCU = 0.5 / 1kB

RCU = 4 / 8 kB

Two switchable billing modes:

Comparing costs

• Avg 1 req / s (2629744 req / month)
  • fits to free tier 3-8x
• Lambda invocation time <100ms
• DynamoDB write / reads <1kB / 8kB

Know your usage patterns!

Expected monthly cost without Free tier:

Lambda: need-to-knows to avoid injury

• request life cycle
• queuing mechanism & auto-scaling
• package size & cold starts
• integration latency & concurrency
• ...and more, but not a focus of this talk

Lambda inside

REQ_A

container

REQ_B

executions

Notes:

• keep integ. latency low to minimize avg. concurrency
• Lambda does not like to wait too long for previous requests to complete

Package size & cold starts

• Cold start = lambda spinning up an container instance
  1. fetch code from S3
  2. unpack
  3. load environment
• 50MB zipped package size limit, 250MB unzipped
  • 5MB package ... 0.8 - 1s
  • 10MB package ... 1 - 1.2s
• => keep your Lambda package as small as possible

Refactoring code

N * req_latency

req_latency

=> "Best practice" becomes a factor-N cost-saving measure

Refactoring infrastructure

Example: Propagating change in data to a slow third party / legacy service

~100ms

10 req/s

10 [requests per second] * 12 [100ms increments] * price_per_100ms

Monthly:  $262

Refactoring infrastructure

Example: Propagating change in data to a slow third party / legacy service

~100ms

10 req/s

(10 [requests per second] * 1 [100ms increments] * price_per_100ms) +
(num_batches * 11 [100ms increments])

Monthly:  $21.9 (new BE cost) + $0.08 (5min batches)

λ

batch

Serverless Economics

Pay-per-request pricing model impacts the way we code & the way we design our applications.

What about impact on business decisions, strategy, ... ?

Example

+num_req * C_ratio * profit_per_C

Assume feature / project usage (num_req) is connected to the revenue stream with some conversion ratio of C_ratio yielding profit_per_C on average:

-num_req * price_per_req

Preferably:

(num_req * C_ratio * profit_per_C) — (num_req * price_per_req) > 0

Example

Preferably:

(num_req * C_ratio * profit_per_C) — (num_req * price_per_req) > 0

Min. conversion ratio to make money:

C_ratio > price_per_req / profit_per_C

Note: no need to know usage beforehand to evaluate viability (or wait & hope for scale to kick in).

Note: number of requests (and possibly conversion rate) are actually functions of time.

Example

profit(t) = (num_req(t) * C_ratio * profit_per_C) —
            (num_req(t) * price_per_req)

Profit as a function of time:

0 = total_expends —   (num_req(t) * C_ratio * profit_per_C) — 
                      (num_req(t) * price_per_req)

Break even:

t_0

t_1

Time to break even:

t_1 — t_0

Note: use expected value from a sampled distribution instead of averages / estimates, if you have the data.