Database Reference
In-Depth Information
1000
us-west-1
us-east-1
eu-west-1
us-west-2
us-east-2
eu-west-2
100
10
1
0.1
0.01
1E-3
1E-4
0
600
1200
1800
2400
3000
Timeline per slave (second)
Fig. 7.12
The performance of the replication delay for up to 6 replica servers with the framework
enabled, delay
tolerance
D
4;000 ms, and int
v
l
mon
D
120 s
that add a new replica server because it is the closest location to the virtualized
database server in
us-west-1
which hosts the replica server that is first to violate
its defined SLA data freshness. The results also show that as the monitor interval
increases, the triggering points for adding new replica servers are usually delayed.
On the contrary, the results of Figs.
7.7
, and
7.10
-
7.12
show that increasing the
value of the tolerance of the replication delay parameter, delay
tolerance
, does not
necessarily cause a delay in the triggering point for adding new replica servers.
7.5
Provisioning the Database Tier Based on SLA
of Transaction Response Times
Another consumer-centric SLA metric that we consider in our framework is the total
execution times of database transactions (response time). In practice, this metric
has a great impact on the user experience and thus satisfaction of the underlying
services. In other words, individual users are generally more concerned about when
their transaction will complete rather than how many transactions the system will
be able to execute in a second (system throughput) [
133
]. To illustrate, assuming a
transaction (T ) with an associated SLA for its execution time (S ) is presented to the
system at time 0, if the system is able to finish the execution of the transaction at
time (t
S ) then the service provider has achieved his target otherwise if (t>S)
then the transaction response cannot be delivered within the defined SLA and hence
a penalty p is incurred. In practice, the SLA requirements can vary between the
different types of application transactions (for example, a login application request
