diff --git a/artifact_evaluation/azure_500/dirigent/INSTRUCTIONS.md b/artifact_evaluation/azure_500/dirigent/INSTRUCTIONS.md
index e23df26..3730920 100755
--- a/artifact_evaluation/azure_500/dirigent/INSTRUCTIONS.md
+++ b/artifact_evaluation/azure_500/dirigent/INSTRUCTIONS.md
@@ -7,10 +7,11 @@ Description: This experiment runs the downsampled Azure trace with 500 functions
 Instructions:
 - Start Dirigent cluster as per instructions located in the root folder of artifact evaluation instructions.
 - On the `node0` execute `mkdir -p ~/invitro/data/traces/azure_500` or `mkdir -p ~/invitro/data/traces/azure_500_firecracker`, depending on which runtime you use. 
-- Copy traces to `node0` using `scp azure_500/* user@node0:~/invitro/data/traces/azure_500/` or `scp azure_500_firecracker/* user@node0:~/invitro/data/traces/azure_500_firecracker/`.
-- Make sure on `node0` `~/invitro` branch is `rps_mode`. With text editor open `cmd/config_dirigent_trace.json` and change TracePath to match `azure_500` or `azure_500_firecracker`.
+- Copy traces from this folder to `node0` using `scp azure_500/* user@node0:~/invitro/data/traces/azure_500/` or `scp azure_500_firecracker/* user@node0:~/invitro/data/traces/azure_500_firecracker/`.
+- Make sure on `node0` `~/invitro` branch is `rps_mode`. With text editor open `~/invitro/cmd/config_dirigent_trace.json` and change TracePath to match `azure_500` or `azure_500_firecracker`.
 - On your local machine run `./scripts/start_resource_monitoring.sh user@node0 user@node1 user@node2`. 
-- Run the load generator in `screen` on `node0` with `cd ~/invitro; go run cmd/loader.go --config cmd/config_dirigent_trace.json`. Wait until the experiment completed (~30 minutes). There should be ~170K invocations, with a negligible failure rate.
+- Run the load generator in screen/tmux on `node0` with `cd ~/invitro; go run cmd/loader.go --config cmd/config_dirigent_trace.json`. Wait until the experiment completed (~30 minutes). There should be ~170K invocations, with a negligible failure rate.
 - Gather experiment results. Make sure you do not overwrite data from the other experiment, and you place results in correct folders.
+  - Create folders for storing results with `mkdir -p ./artifact_evaluation/azure_500/dirigent/results_azure_500` and `mkdir -p ./artifact_evaluation/azure_500/dirigent/results_azure_500_firecracker`
   - Copy load generator output with `scp user@node0:~/invitro/data/out/experiment_duration_30.csv results_azure_500/`
   - Copy resource utilization data with `mkdir -p ./artifact_evaluation/azure_500/dirigent/results_azure_500/cpu_mem_usage && ./scripts/collect_resource_monitoring.sh ./artifact_evaluation/azure_500/dirigent/results_azure_500/cpu_mem_usage user@node0 user@node1 user@node2`.
diff --git a/artifact_evaluation/azure_500/knative/INSTRUCTIONS.md b/artifact_evaluation/azure_500/knative/INSTRUCTIONS.md
index 6fbf542..dcd92ec 100644
--- a/artifact_evaluation/azure_500/knative/INSTRUCTIONS.md
+++ b/artifact_evaluation/azure_500/knative/INSTRUCTIONS.md
@@ -11,7 +11,8 @@ Instructions:
 - On `node0` create a directory where trace will be stored `cd invitro; mkdir data/traces/azure_500`.
 - Copy the trace from folder where this instruction file is located to the folder you previously created on `node0` using the following command `scp azure_500/*.csv user@node0:~/invitro/data/traces/azure_500`. 
 - On your local machine run `./scripts/start_resource_monitoring.sh user@node0 user@node1 user@node2`.
-- On `node0` run `screen` and inside the `screen` run `go run cmd/loader.go --config cmd/config_knative.json`. Function deployment will take 10-20 minutes, and then experiment will run for additional 30 minutes.
+- On `node0` inside screen/tmux run `cd ~/invitro; go run cmd/loader.go --config cmd/config_knative.json`. Function deployment will take 10-20 minutes, and then experiment will run for additional 30 minutes.
 - Gather experiment results. Make sure you do not overwrite data from the other experiment, and you place results in correct folders.
+  - Create a folder for storing results with `mkdir -p ./artifact_evaluation/azure_500/knative/results_azure_500`
   - Copy load generator output with `scp user@node0:~/invitro/data/out/experiment_duration_30.csv results_azure_500/`
   - Copy resource utilization data with `mkdir -p ./artifact_evaluation/azure_500/knative/results_azure_500/cpu_mem_usage && ./scripts/collect_resource_monitoring.sh ./artifact_evaluation/azure_500/knative/results_azure_500/cpu_mem_usage user@node0 user@node1 user@node2`.
\ No newline at end of file
diff --git a/artifact_evaluation/cold_start_sweep/knative/INSTRUCTIONS.md b/artifact_evaluation/cold_start_sweep/knative/INSTRUCTIONS.md
index 06ab4dd..571b026 100644
--- a/artifact_evaluation/cold_start_sweep/knative/INSTRUCTIONS.md
+++ b/artifact_evaluation/cold_start_sweep/knative/INSTRUCTIONS.md
@@ -10,7 +10,7 @@ Instructions:
   - Open `~/invitro/workloads/container/trace_func_go.yaml`, set `autoscaling.knative.dev/max-scale` to `1`, and then set image to `docker.io/cvetkovic/dirigent_empty_function:latest`.
   - Run `kubectl patch configmap config-autoscaler -n knative-serving -p '{"data":{"scale-to-zero-grace-period":"1s","scale-to-zero-pod-retention-period":"1s","stable-window":"6s"}}'`
   - In `~/invitro/cmd/config_knative_rps.json` set `ExperimentDuration` to 2 and `RpsColdStartRatioPercentage` to `100`
-- The command for running experiment for each data point is `cd invitro; go run cmd/loader.go --config cmd/config_knative_rps.json`. Use the following data point settings in `cmd/config_knative_rps.json` for experiments.
+- The command for running experiment for each data point is `cd ~/invitro; go run cmd/loader.go --config cmd/config_knative_rps.json`. Use the following data point settings in `cmd/config_knative_rps.json` for experiments.
   - `RpsTarget=1` with `RpsCooldownSeconds=10`
   - `RpsTarget=2` with `RpsCooldownSeconds=15`
   - `RpsTarget=3` with `RpsCooldownSeconds=20`
diff --git a/scripts/common.sh b/scripts/common.sh
index 900145c..b35fa18 100644
--- a/scripts/common.sh
+++ b/scripts/common.sh
@@ -23,8 +23,8 @@ function RemoteExec() {
 
 function SetupControlPlane() {
     # Start Redis server
-    RemoteExec $1 "sudo docker stop \$(docker ps -aq)"
-    RemoteExec $1 "sudo docker rm \$(docker ps -a -q)"
+    RemoteExec $1 "sudo docker stop \$(sudo docker ps -aq)"
+    RemoteExec $1 "sudo docker rm \$(sudo docker ps -a -q)"
     RemoteExec $1 "sudo docker run -d --name redis-stack-server -p 6379:6379 redis/redis-stack-server:latest"
 
     RemoteExec $1 "cd ~/cluster_manager; git pull"
diff --git a/scripts/setup.cfg b/scripts/setup.cfg
index 449d561..8683bce 100644
--- a/scripts/setup.cfg
+++ b/scripts/setup.cfg
@@ -8,4 +8,4 @@ FAKE_WORKER_MODE=0
 DAEMONS_PER_NODE=1
 
 # Choose from [containerd, firecracker]
-WORKER_RUNTIME="firecracker"
\ No newline at end of file
+WORKER_RUNTIME="containerd"
\ No newline at end of file
diff --git a/scripts/start_resource_monitoring.sh b/scripts/start_resource_monitoring.sh
index 24f926c..837f885 100755
--- a/scripts/start_resource_monitoring.sh
+++ b/scripts/start_resource_monitoring.sh
@@ -1,8 +1,10 @@
 #!/bin/bash
 
+readonly DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" > /dev/null 2>&1 && pwd)"
+
 function internal() {
     # Connect to the remote machine and start a tmux session
-    scp /home/lcvetkovic/projects/cluster_manager/cmd/monitoring/monitoring.py $1:~/monitoring.py
+    scp $DIR/../cmd/monitoring/monitoring.py $1:~/monitoring.py
 
     ssh $1 "tmux kill-session -t resource_monitoring"
     ssh $1 "tmux new-session -d -s resource_monitoring"